Browse Items (7684 total)
Sort by:
-
The 90-h workweek controversy at L&T: leadership, culture and the future of work in India
Learning outcomes Upon completion of this case, students will be able to understand the implications of psychological contract theory in organizational contexts. It will allow them to analyse how leadership communication affects internal trust and public perception and critically evaluate the reputational consequences of symbolic leadership behaviour. Case overview/synopsis S.N. Subrahmanyan, Chairman and Managing Director of Larsen & Toubro (L&T), Indias leading engineering conglomerate, made a public statement encouraging employees to work 90?h a week and use Sundays to achieve global excellence. Although intended as a motivational message, the statement triggered nationwide backlash. Employees, industry leaders and the public interpreted the comment as reflecting an outdated, unsustainable work culture, sparking debates around worklife balance and generational shifts in employee values. Internally, the comment created anxiety and ambiguity regarding the companys expectations, especially among younger professionals. The case will allow students to examine how leadership communication can reshape psychological contracts, explore generational tensions in the workplace and evaluate how organizations should respond to reputational challenges while preserving performance culture. The case dilemma centres on whether L&T should clarify, retract or reinforce the chairmans statement. Complexity academic level This case is appropriate for upper undergraduate- and graduate-level programs in organizational behaviour, strategic human resource management, business ethics and leadership studies. Potential programs include, BBA, MBA HR and industrial and organizational psychology. Supplementary Material Teaching notes are available for educators only. Subject code CSS 6: Human Resource Management. 2025 Emerald Publishing Limited -
Exploring the mediating role of job and life satisfaction between workfamily conflict, familywork conflict and turnover intention
Purpose: This study investigates the influence of work-to-family and family-to-work conflict on turnover intention (career break), mediated through job and life satisfaction among Indian women in the service sector, using role conflict theory as the base. Design/methodology/approach: A total of 421 usable responses from women who had taken a career break were collected using a 36-item scale from six major metro cities in India through social and digital media platforms. A purposive-cum-snowballing sampling method was adopted. The hypotheses were tested using structural equation modeling (SEM) through AMOS. Findings: Findings suggest that job satisfaction (JS) is a significant predictor of turnover intention, both when work spills into the family domain, and family responsibilities spill into the work domain, thereby confirming the mediating influence of JS. Interestingly, life satisfaction (LS) only seems to mediate between inter-domain conflict and turnover intention partially. Research limitations/implications: This is a descriptive study, and is thereby limited in terms of its generalizability, specifically as it included respondents only from six major metro cities in India. Practical implications: The extended work-family conflict model could help managers structure organizational interventions that support women to deal with the challenges of managing the demands of both work and family domains, thereby reducing the negative influence on JS. Such initiatives could help reduce career breaks among women. Originality/value: We explored the cause of career breaks among Indian urban women employed in the service sector, using the extended model of inter-role conflict and their attitudes towards both life and job. 2024, Emerald Publishing Limited. -
Exploring the factors of learning organization in school education: therole of leadership styles, personalcommitment, andorganizational culture
Purpose: This study aims to test the conceptual model of the factors of learning organization and explore the degree of mediation of organizational culture in the relationship between leadership styles, personal commitment, and learning organization in school education. Design/methodology/approach: The learning organization profile (LOP) and OCTAPACE profile served to measure learning organization and organizational culture, respectively. The researchers developed scales to measure principals leadership styles and teachers personal commitment. Data included 750 school teachers. Findings: This study found a good fit in the proposed conceptual model. The organizational culture had a significant mediating effect on the path of leadership styles and learning organization and a significant mediating effect on the path of personal commitment and learning organization. Originality/value: To promote a more comprehensive learning culture, school principals should consider two specific organizational mechanisms: the intangible cultural components (such as corporate values, beliefs, and norms) and the tangible structural components (such as organizational structure and workflow systems). These two domains play a crucial role in creating a conducive learning environment. 2024, Jacqueline Kareem, Harold Andrew Patrick and Nepoleon Prabakaran. -
Does the relationship between sustainable human resource management and organizational identification vary by culture? Evidence from 35 countries based onGLOBE framework
Purpose The article discusses the relationships between sustainable HRM and organizational identification, conceptualized at the individual level, and the moderating role of cultural dimensions conceptualized at the country level (described in GLOBEs framework). The studys theoretical model based on social exchange theory proposes that sustainable HRM practice increases organizational identification. However, the strength of this identification depends on the dimensions of national culture. Thus, we assumed national culture functions as a second-level moderator in the relationship between sustainable HRM and organizational identification. Design/methodology/approach We conducted the study with data from 10, 421 employees across 35 countries. We used a multilevel modeling approach for data analysis. Findings The study revealed the cross-level interaction effects of national culture on the relationship between sustainable HRM practice and organizational identification. Specifically, the results indicate that sustainable HRM strengthens employees organizational identification more in cultures with higher levels of gender egalitarianism and lower levels of humane orientation. Originality/value This study demonstrates that the relationship between sustainable HRM practices and employees organizational identification is culturally sensitive. It highlights the need to consider cultural context when assessing the impact of sustainable HRM practices on employee outcomes. Furthermore, it shows that certain cultural dimensions can enhance the effect of sustainable HRM practices. 2025 Dariusz Turek et al. Published by Emerald Publishing Limited. -
Unveiling the response of food inflationto the economic policy uncertainty, energy price shocks andcarbon emission
Purpose This research paper examines the impact of economic policy uncertainty, energy price shocks and carbon emissions on food inflation from a global perspective, for the period of 20012023. Design/methodology/approach To calibrate the economic policy uncertainty, carbon emissions and energy price shock, we apply the economic uncertainty index of Baker etal. (2016), carbon dioxide in a million tonnes and the energy price index. Finally, to accomplish the relevant objectives, we exert the panel autoregressive distributed lag (ARDL) and panel Granger non-causality model. Findings We can summarise the key empirical insights from this pragmatic examination as follows: Initially, the panel ARDL outcome suggests that in the long-run, economic policy uncertainty and energy inflation positively influence food inflation. The result further reveals that a surge in economic policy uncertainty and energy inflation would lead to an increase in food prices in the long run in these panel countries. Secondly, the relevant outcome demonstrates that, in the long run, carbon emissions do not have a significant impact on food prices across the panel nation. Finally, the causality analysis concludes that there is unidirectional causality from energy inflation, carbon emissions and economic policy uncertainty to food inflation. Originality/value This investigation aims to add three aspects to the theme of food inflation. First of all, we endeavour to capture the presence of the underlying impact of economic policy uncertainty, energy price shock and carbon emissions on food prices. Second, current research extends the literature by employing panel data econometric analysis in the above context. Furthermore, our research is novel in that we consider carbon emissions to reveal their impact on food prices, whereas none of the previous analyses ever contemplated the impact of carbon emissions on food prices. Finally, by extending this analysis to a heterogeneous economic outlook that includes both advanced and emerging economies globally, it provides policymakers with a clear understanding of an effective strategy for managing food inflation and achieving sustainability. 2025 Emerald Publishing Limited -
Which is the green generation? Amultigroup analysis of millennials and Generation Zs green consumerism
Purpose This study aimed to investigate how components of green marketing mix (GMM), green product (GPD), green price (GPC), green place (GPL) and green promotion (GPM) influence consumer attitudes (ATT), subjective norms (SNM), perceived behavioural control (PBC) and purchase intention (PI) and finally green consumerism (GCM). Design/methodology/approach Using Smart PLS 4 software and PLS-SEM approach, data were analysed for structural relationships among the components of GMM, ATT, SNM, PBC, PI and GCM. The model evaluates hypotheses linking GPD, GPC, GPL and GPM to ATT, SNM and PBC and examines how ATT, SNM and PBC affect PI and GCM. Findings The study revealed that GMM, as a higher-order construct, positively impacts ATT, SNM and PBC, while ATT, SNM and PBC partially mediate the relation between GMM and PI. PI then ultimately results in GCM. The multigroup analysis indicated there is no significant difference between the age groups examined. Research limitations/implications The study may not generalize to all industries or regions. Future research could explore additional factors like cultural or technological influences, and longitudinal studies may be conducted. Practical implications As environmental concerns grow, marketers should focus on consumer attitudes towards green products. Aligning green attributes with consumer values, transparent pricing and multi-channel communication can enhance ATT, SNM and PBC over green purchases, fostering acceptance and intention. Social implications While the findings promote GCM, their broader impact is contingent on genuine environmental practices. Without systemic changes in production and policy, GCM risks perpetuating superficial sustainability narratives. Originality/value This study advances the field by investigating how GMM influences purchase intentions (PI) among Indias urban Millennials and Generation Z, two generations pivotal to shaping sustainable consumption trends in a high-pollution economy. 2025 Emerald Publishing Limited -
Myths and magic of adopting marketing technologies: acustomer-centric framework
Purpose This study seeks to explore how customers perceptions of the benefits, risks and continuation intention toward Marketing Technologies (MarTech) influence their actual usage. This research study utilizes the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework for assessing the usage and continuation intention (intention behavior) of customers toward adopting marketing technologies. Design/methodology/approach Data was collected from 266 respondents and analyzed using partial least squares structural equation modeling (PLS-SEM). A post-hoc analysis was undertaken using importance-performance matrix analysis (IPMA) to assess the importance and performance of determinants in the PLS-SEM model. Findings The results of the study indicate that perceived usefulness, perceived enjoyment and social influence have positive effects on Marketing Technologies (MarTech) usage intention. Additionally, usage intention has no effect on continuation intention. The performance of Perceived Usefulness is 74.879, which is higher than other constructs and ascertains that perceived usefulness contributes largely to predicting MarTech continuation intention. Originality/value This study enriches the technology adoption literature by investigating the predictors of marketing technologies (MarTech) adoption and usage from the perspective of customers. Notably, the novelty of this research lies in investigating the impact of perceived trust and perceived risk on MarTech usage and continuation intention of customers. 2025 Emerald Publishing Limited -
Voluntary cybersecurity risk disclosures and firms characteristics: the moderating role of the knowledge-intensive industry
Purpose: This study examines voluntary cybersecurity risk disclosures (VCRD) by listed Indian companies. It also investigates how it relates to firm-specific characteristics such as size, leverage, profitability, liquidity, beta, market growth and industry. Design/methodology/approach: The extent of VCRD was measured by assessing the cumulative occurrence of cybersecurity risk keywords in the annual report of 100 listed Indian non-financial companies. Keyword extraction and occurrence counts were performed using Python software. A multiple regression analysis was applied to predict the characteristics of VCRD. Findings: The results showed that the theoretical frameworks underpinned by agency and signalling theories continued to provide a valid explanation of VCRD by Indian companies. Specifically, the findings emphasized the importance of firm size, leverage, and beta as significant VCRD determinants. Additionally, the study found that knowledge-intensive industries had a favourable impact on the extent of VCRD. Research limitations/implications: This study is relevant because it informs company management, regulators and investors about the nature and characteristics of companies that satisfy stakeholder demands to prevent cyber breaches. Originality/value: Understanding disclosure characteristics is crucial from policy and regulatory perspectives. Studies on cybersecurity disclosures are related to developed economies such as the United States of America and Canada. This is the first study to explore this issue in a developing nation, in general, and in India, in particular, where cybersecurity risk disclosure has yet to be recognized. 2025, Harmandeep Singh. -
AI in creating inclusive work environments for neurodiverse employees
Purpose This study aims to examine the increased focus on neurodiversity in contemporary businesses. It shows how inclusive policies can capitalize on the special abilities of people with neurodiverse backgrounds, including their extraordinary problem-solving abilities, meticulous attention to detail and creative thinking. These policies benefit the individuals and contribute to a more diverse and innovative workplace. Design/methodology/approach Data was collected through semistructured interviews with HR experts and neurodivergent employees. The qualitative data were manually analyzed and coded, and themes were identified. Findings The results highlight the significant benefits of accepting neurodiversity in the workplace, enlightening the audience about its potential. For instance, artificial intelligence (AI) can be used to anonymize resumes, removing potential biases related to gender, ethnicity or age. In addition, AI can help in identifying the unique skills and strengths of neurodivergent employees, enhancing the fit between job responsibilities and their abilities. This study also emphasizes the wider effects of accepting neurodiversity on employee satisfaction, productivity and organizational innovation. This study promotes a deep learning framework that combines human-centered strategy with strategic methods to maximize the participation of neurodiverse workers and foster a more creative and dynamic corporate culture, convincing the audience of its benefits. Research limitations/implications This study is limited by its qualitative nature and relatively small sample size, comprising 15 HR professionals and 20 neurodivergent employees, which restricts generalizability. The sensitive nature of neurodiversity also made participant recruitment challenging, with some individuals hesitant to disclose their condition. In addition, companies were reluctant to share internal AI practices due to confidentiality concerns. The research focused on a select set of organizations, primarily from specific regions, limiting cross-cultural applicability. Furthermore, the absence of AI developers in the sample means insights into technical tool design and implementation remain unexplored, suggesting a gap for future multidisciplinary research. Practical implications This study provides actionable insights for HR professionals and organizational leaders aiming to improve neurodiverse hiring and support systems. It identifies specific AI tools such as Grammarly, Otter.ai and Pymetrics, that can be integrated into recruitment and workplace settings to enhance communication, reduce sensory overload and match roles to individual strengths. Organizations can use the deep learning framework proposed to design more inclusive policies and infrastructure. Training managers and customizing AI-driven accommodations can improve retention, engagement and performance among neurodiverse talent. This research supports firms in developing more equitable, adaptive and innovative environments aligned with diversity and inclusion goals. Social implications This study promotes a societal shift in how neurodivergent individuals are perceived and supported in the workforce. By emphasizing ability over deficit and proposing inclusive AI integration, it helps reduce stigma and encourages broader acceptance of cognitive diversity. The findings advocate for universal accommodations that do not require self-disclosure, promoting dignity and equity. Improved employment outcomes for neurodiverse individuals contribute to economic inclusion, reduce unemployment rates and challenge ableist norms. The research also aligns with broader Diversity Equity and Inclusion (DEI) movements, inspiring organizations and policymakers to build socially responsible frameworks that reflect the value of every individual, regardless of neurological difference. Originality/value This paper offers original value by exploring the underresearched intersection of AI and neurodiversity inclusion in the workplace. It contributes novel insights through qualitative analysis of HR professionals and neurodivergent employees, highlighting the role of AI in reducing hiring bias, customizing work environments and enhancing employee well-being. By proposing a deep learning framework and cataloging AI tools matched to neurodiverse conditions, this study bridges theory and practice. It uniquely positions AI as both a technological and ethical enabler for inclusive employment, making it highly relevant for scholars, practitioners and policymakers aiming to foster equitable, future-ready workplaces. 2025 Emerald Publishing Limited -
A multi-cognitive approach to empowering secondary school teachers' self-efficacy and practices related to education for sustainable development
Purpose Education for Sustainable Development (ESD) is vital for addressing global sustainability goals. However, integration in Indian schools faces challenges, particularly due to gaps in teacher preparedness. This study aimed to evaluate the effectiveness of a multi-cognitive approach (MCA) in empowering secondary school teachers' self-efficacy and ESD integration. Design/methodology/approach A quasi-experimental, one-group pretestposttest design was employed with 50 secondary school teachers from marginalized communities in Kerala, India. Participants with over 6years of experience but no prior ESD training underwent a 3-month MCA-based transformative learning program. The intervention addressed content, perspectives, processes and design. Teacher self-efficacy and ESD practices were measured pre- and immediately post-intervention, and three months later, using structured questionnaires. Findings Teachers' self-efficacy significantly improved post-intervention (52.707.61) and was sustained at three months (56.604.59), compared to baseline (49.069.69) (p<0.001). ESD-related practices also improved post-intervention (47.487.16), with further gains at three months (51.863.96), compared to pre-intervention (41.905.91). Research limitations/implications These results support incorporating the MCA into teacher training and professional development programs to foster sustainable education practices. The approach aligns with SDG 4.7 and can guide policy reforms in integrating ESD into mainstream education. Practical implications The study also presents a professional development model for schools, particularly beneficial in resource-constrained contexts, that enables teachers to embed sustainability in their practices. Furthermore, it offers policy guidance for embedding MCA-informed ESD into teacher education and national curricula, supporting Sustainable Development Goal 4.7 and NEP 2020 vision, promoting systemic education reform in sustainability. Social implications This study empirically validates an MCA as an effective framework for ESD. It highlights those engaging teachers across the cognitive, reflective, procedural and design dimensions, simultaneously enhancing their self-efficacy and sustaining ESD practices. The findings extend existing theories by showing that self-efficacy in sustainability is teachable and durable with the right interventions. Originality/value This study highlights MCA as a promising model for building teacher capacity in ESD and recommends future research on its impact on student outcomes. Emerald Publishing Limited -
Condensate phases of nuclear matter from AdS hardwall models
This work develops our previous study of confined phases at finite densities in AdS/QCD by systematically exploring the possibility of baryonic condensates. Using phenomenologically motivated boundary conditions in an AdS hardwall model, we show that both baryonic and quark-type condensates dominate the phase diagram at low temperatures. We also undertake a careful scan of the parameter space to extract robust conclusions. (2025), (American Physical Society). All rights reserved. -
Investigating wave propagation across loosely bonded interfaces in visco-piezo composites with flexoelectricity in LiNbo3 and AlN
This study compares the transference of surface seismic waves at the loosely bonded interface of a visco-piezo composite structure using two materials, lanthanum niobate (LiNbO 3) and aluminium nitride (AIN). The structure comprises a viscoelastic layer bonded to a piezoelectric substrate, incorporating the flexoelectric effect. The shear response of the upper layer is modelled using three rheological models: Kelvin-Voigt, Maxwell and Newton. An analytical separable variable method is employed to derive complex dispersion relations for both electrically open- and short-circuit conditions. The numerical analysis focuses on the influence of key parameters, such as bonding conditions and interfacial parameters, on phase velocity and attenuation coefficients in both materials. Results indicate that AIN shows higher phase velocities, while LiNbO 3 demonstrates a stronger impact on attenuation, particularly in the Kelvin-Voigt model. In addition, the flexoelectric effect significantly alters the wave behaviour in both materials, impacting both phase velocity and attenuation. This comparison reveals important differences in wave propagation behaviour, which is crucial for the development of devices like sensors, actuators and energy harvesters. The study offers new insights into piezo-flexo coupling and its potential applications in advanced piezoelectric systems. 2025 The Author(s). -
Eco-friendly synthesis of NiO and Ag/NiO nanoparticles: Applications in photocatalytic and antibacterial activities
Herein, NiO and Ag/NiO NPs were produced via the solution combustion method using nickel nitrate and silver nitrate as oxidizers and Cocos nucifera water as a fuel at 450C. The study also explores their applications in photocatalytic dye degradation, H 2 production and antibacterial properties. The primary advantage of using C. nucifera water as a green fuel in the solution combustion method is that it serves a dual purpose - both as a fuel and as a solvent. This eliminates the need for additional water to create a homogeneous redox mixture of fuel and oxidant in the experimental procedure. X-ray diffraction confirmed the existence of Ag in the bunsenite form of rhombohedral structure with a simple cubic system, with particles sized at 31-44 nm. Energy-dispersive X-ray spectroscopy revealed Ni, O and Ag weight percentages of 48.2, 44.5 and 7.3%, respectively. X-ray photoelectron spectroscopy confirmed the formation of Ag in NiO nanostructure. UV-visible spectrometry showed reduced band gap energy of Ag/NiO NPs (3.03-2.87 eV) compared to the bare NiO NPs (3.21 eV), red shift of the optical response towards the visible region after doping Ag into the NiO. The 0.3 wt% Ag/NiO NPs showed the highest quantum efficiency (0.781) among the other synthesized NPs. Fourier-transform infrared spectroscopy revealed absorption bands in the range of 460-900 cm -1 stretching vibrations of Ni-O and Ag-O. Photoluminescence spectroscopy indicated that a doping concentration of 0.3 wt% Ag effectively introduces donor levels, defect levels and surface trap states within the NiO nanocrystalline structure, enhancing charge carrier separation and reducing recombination. Scanning electron microscopy revealed a voluminous, porous surface morphology characterized by numerous voids, resulting from the release of various combustible gases during the combustion process. Transmission electron microscopy images showed that most particles were spherical, irregular in size and well-distributed, with minimal aggregation with an average particle size of 25.8 nm. BET analysis of both NiO and 0.3 wt% Ag/NiO NPs exhibited type IV adsorption isotherms, indicating mesoporous structures and a clear monolayer-multilayer adsorption process, 0.3 wt% Ag/NiO NPs showed the highest surface area (170 m2 g-1) compared to the NiO (130 m2 g-1) NPs. Ag/NiO NPs has demonstrated a promising H2 evolution rate of 1212 ?mol g-1 under visible light illumination in a water/ethanol system. The trypan blue dye degradation reaches up to 98% and has moderate stability for the reusable photocatalysis process. The synthesized NPs exhibited significantly enhanced antibacterial activity against a range of bacterial strains. 2025 The Authors. -
Dispositional Mindfulness and Perceived Stress in Psychiatric and Nonpsychiatric Physicians: A Facet-level Pilot Study
OBJECTIVES: Perceived stress is a significant concern among health care professionals, with potential consequences for mental health and clinical performance. This study examined associations between dispositional mindfulness and perceived stress among Indian physicians working in psychiatric and nonpsychiatric specializations within hierarchical systems with limited institutional support. METHODS: In this cross-sectional pilot study, 62 clinicians (39 nonpsychiatric and 23 psychiatric physicians) completed the Perceived Stress Scale and the Five Facet Mindfulness Questionnaire-Short Form. Independent samples t tests compared perceived stress and mindfulness scores between the groups. Correlations and linear regression analyses were conducted to examine relationships between mindfulness and perceived stress. RESULTS: No statistically significant differences were found between psychiatric and nonpsychiatric physicians in perceived stress, t(59)=0.98, P=0.329, d=0.27, or total mindfulness, t(59)=-1.31, P=0.186, d=0.35. Across the sample, higher dispositional mindfulness was strongly associated with lower perceived stress, r(60)=-0.65, P<0.001, r=0.43, particularly for the Describe and Acting with Awareness facets. Linear regression indicated that mindfulness was significantly related to perceived stress, ?=-0.65, t=-6.66, P<0.001, accounting for 42.5% of the variance. CONCLUSIONS: These findings cautiously suggest that dispositional mindfulness may serve as a potential psychological resource for stress regulation and burnout prevention among clinicians. Further research is warranted to validate these associations in larger and more diverse samples and to explore practical applications within wellness initiatives. Copyright 2026 Wolters Kluwer Health, Inc. All rights reserved. -
Golden orator to tongue cancer survivor: A case study tracing identity transformation through religious coping
The "survivorship" identity corresponds to a collective identity for individuals that have experienced cancer. While medical labels, culture and personal beliefs influence this label, this case report illuminates the journey of integrating the preillness identity to a postrecovery identity through the long-Term survivorship experience of T.J.J, a nonagenarian cancer survivor and Indian priest belonging to the Syrian Marthomite Christian denomination, focusing on how religious coping mechanisms facilitated identity reintegration. Diagnosed with tongue cancer at age 64 years, T.J.J.Transitioned from a renowned orator to a religious writer, reshaping his identity through eudemonic principles of purpose, self-Actualization, and growth. The influence of religious meaning-making, prayer, and communal support is highlighted, which helped cognitively reframe his experience of loss into a transformative experience that fostered psychological security. Implications for public health policies emphasize incorporating religious coping strategies in culturally relevant survivorship programs for better psychosocial outcomes. 2025 Lippincott Williams and Wilkins. All rights reserved. -
AI-Enabled Early Detection of Chemo-Induced Cardiotoxicity Patterns Using ECG Time Series Data
Objectives: Chemotherapy-induced cardiotoxicity is still a major clinical problem, usually appearing subclinically before structural or symptomatic cardiac dysfunction appears. Standard surveillance methods use imaging and biomarkers, which are time-intensive and money-intensive and can only identify damage at more advanced levels. Electrocardiography (ECG) provides a low-cost, non-invasive method that can detect early electrophysiological changes but is not fully utilized in cardio-oncology. The present work was designed to build an explainable machine learning model for predicting chemo-like cardiotoxicity patterns at an early stage from single-lead ECG signals. Methods: A public ECG data set (n=4997 segments) underwent preprocessing and was converted to 18 temporal, morphologic, and spectral features. Two ensemble learning algorithmsRandom Forest and XGBoostwere trained and validated with stratified splits. Model performance was assessed with ROCAUC, PRAUC, and F1-score with 1000 bootstrap resampling. Feature interpretability was evaluated through permutation importance and SHAP analysis. Results: Both models scored near-perfect classification (ROCAUC and PRAUC>0.99, F1-score ? 0.986). Spectral entropy, band3 (high-energy frequency), QT surrogate, and peak count were the top features ranking alongside early cardiotoxicity indicators like repolarization instability and autonomic imbalance. Conclusions: The feature-driven, interpretable ML architecture suggested here shows that single-lead ECG has the potential to be an affordable and clinically relevant tool for the early detection of chemotherapy-induced cardiotoxicity. The method provides a feasible route toward implementation in precision cardio-oncology, particularly in resource-poor or ambulatory environments. 2025 -
Predicting and Optimizing Synergistic Drug Combinations for Breast Cancer Treatment Using Machine Learning
Objectives: The study aims to identify highly synergistic drug combinations for breast cancer treatment using machine learning models. The primary objective is to predict drug synergy scores accurately and rank combinations with the highest potential for therapeutic efficacy. Methods: Machine learning models, including XGBoost, Random Forest (RF), and CatBoost (CB), were employed to analyze breast cancer drug combination data. Four synergy metricsZIP, Bliss, Loewe, and HSAwere used to quantify drug interaction effects. The models were trained to predict these synergy scores, and their performance was evaluated using normalized root mean squared error (NRMSE) and Pearson correlation coefficient. Predicted top-ranking drug combinations were further validated by comparing observed versus expected dose-response curves and calculating the area under the curve (AUC) for synergy assessment. Results: XGBoost (XGB_5235) outperformed other models, achieving an NRMSE of 0.074 and a Pearson correlation of 0.90 for the Bliss synergy model. Based on average synergy scores, the top 20 drug combinations were identified, with Ixabepilone+Cladribine, SN 38 Lactone+Pazopanib, and Decitabine+Tretinoin emerging as the most promising. These combinations showed high synergy and were supported by biological insights into their mechanisms of action. Conclusions: The study demonstrates the effectiveness of machine learning in predicting synergistic drug combinations for breast cancer. By accelerating the screening process and reducing experimental burden, the approach offers a promising tool for guiding future in vitro and in vivo validation of combination therapies. Copyright 2025 Wolters Kluwer Health, Inc. All rights reserved.