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Medical Awareness in Telemedicine: A Legal Perspective
Telemedicine is the technology to provide remote delivery of the healthcare services such as consultation, diagnosis, treatment, etc., to the individuals. It is done through telecommunication technology such as video call, audio calls, messaging. It will help in providing the services, especially in rural or underserved areas, while maintaining patient-provider communication and continuity of care. Medical negligence in telemedicine is an emerging area of concern as healthcare increasingly shifts toward virtual platforms. In order to attract the liability under medical negligence, various essentials such as duty of care, breach of duty, causation and damages must be fulfilled. This paper aims to analyse various legal and ethical challenges that could be faced by the individuals in the process of telemedicine. This research paper was created using the doctrinal approach of research. In order to comprehend, analyze, and organize the law, this research style focuses on analyzing legal doctrines, legislation, case laws, and legal principles. The medical negligence in telemedicine could be in several ways such as misdiagnosis or delayed diagnosis, lack of informed consent, failure to refer the patient for in-person treatment, improper prescription or data breaches. These factors complicate diagnosis, treatment, and legal accountability in virtual healthcare settings, increasing risks for both patients and providers. The Author(s). -
Medical image classification using MRI: An investigation
The main objective of the paper is to review the performance of various machine learning classification technique currently used for magnetic resonance imaging. The prerequisite for the best classification technique is the main drive for the paper. In magnetic resonance imaging, detection of various diseases might be simple but the physicians need quantification for further treatment. So, the machine learning along with digital image processing aids for the diagnosis of the diseases and synergizes between the computer and the radiologist. The review of machine learning classification based on the support vector machine, discrete wavelet transform, artificial neural network, and principal component analysis reveals that discrete wavelet transform combined with other highly used method like PCA, ANN, etc., will bring high accuracy rate of 100%. The hybrid technique provides the second opinion to the radiologist on taking the decision. Springer Nature Switzerland AG 2019. -
Medical Image Security Using Dual Encryption with Oppositional Based Optimization Algorithm
Security is the most critical issue amid transmission of medical images because it contains sensitive information of patients. Medical image security is an essential method for secure the sensitive data when computerized images and their relevant patient data are transmitted across public networks. In this paper, the dual encryption procedure is utilized to encrypt the medical images. Initially Blowfish Encryption is considered and then signcryption algorithm is utilized to confirm the encryption model. After that, the Opposition based Flower Pollination (OFP) is utilized to upgrade the private and public keys. The performance of the proposed strategy is evaluated using performance measures such as Peak Signal to Noise Ratio (PSNR), entropy, Mean Square Error (MSE), and Correlation Coefficient (CC). 2018, Springer Science+Business Media, LLC, part of Springer Nature. -
Medical negligence and consumer rights: An analysis /
Law Mantra Journal, Vol.1, Issue 10, pp.500-509, ISSN No: 2321-6417. -
Medical negligence: A lego-economic analysis /
Golden Research Thoughts Vol.2,Issue 6, pp.1-6 ISSN No. 2231-5063 -
Medical plugs to track health using artificial intelligence and IOT /
Patent Number: 341063-001, Applicant: Dr. T Padmapriya. -
Medical Tourism in South India - A Relative Study of the Principal participants in hospital and hospitality industry in South India
International Journal of Management, IT and Engineering Vol.3, ISSUE 1, pp. 613-626 ISSN No. 2249-0558 -
Medical Ultrasound Image Segmentation Using U-Net Architecture
This research article discusses the implementation aspects of a Deep Learning architecture based on U-Net for medical image segmentation. A base model of the U-Net architecture is extended and experimented. Unlike the existing model, the input images are enhanced by applying a Non-Local Means filter optimized using a metaheuristic Grey wolf optimization method. Further, the model parameters are modified to achieve better performance. Tests were performed using two benchmark B-mode Ultrasound image datasets of 200 Breast lesion images and 504 Skeletal images. Experimental results demonstrate that the modifications resulted in more accurate segmentation. The performance of the modified implementation is compared with the base model and a Bidirectional Convolutional LSTM architecture. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Medical waste treatment device /
Patent Number: 354500-001, Applicant: Ila Anand. -
Medical waste treatment device /
Patent Number: 354500-001, Applicant: Ila Anand. -
Medical waste treatment device /
Patent Number: 354500-001, Applicant: Ila Anand. -
Medicinal Exploitation of Coriandrum sativum L.
Coriandrum sativum L. is a potential herb that is commonly known as coriander or Chinese parsley is being possessed to have various medicinal properties. Almost all the parts of the herb have been examined for its effectiveness in various human diseases such as migraine, hypertension and diabetes specifically. The diseases considered for the current review are migraine, hypertension and diabetes, which are highly prevalent as well as major co-morbidity for other clinical conditions. The extracts of different parts of C. sativum have been identified to have roles in treating and managing migraine, hypertension and diabetes. The genetic inter-relationship of C. sativum with the diseases are also being discussed in this review. The literature surf was done in platforms for the journals life science and medicinal research using the keywords C. sativum, herbal medicine, anti-diabetic, anti-hypertensive, migraine, genetics etc. The results obtained through the clinical trials conducted by various researchers globally were satisfactorily acceptable in treating these diseases along with some other diseases to a certain extent, whereas the genetic studies were insignificant. Henceforth, the current literature review highlights the medicinal exploitation of C. sativum in accordance with the treatment and management of migraine, hypertension and diabetes. 2022 Visagaa Publishing House. -
Medicinal plants, phytochemicals, and herbs to combat viral pathogens including sars-cov-2
The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome corona virus-2 (SARS-CoV-2), is the most important health issue, internationally. With no specific and effective antiviral therapy for COVID-19, new or repurposed antiviral are urgently needed. Phytochemicals pose a ray of hope for human health during this pandemic, and a great deal of research is concentrated on it. Phytochemicals have been used as antiviral agents against several viruses since they could inhibit several viruses via different mechanisms of direct inhibition either at the viral entry point or the replication stages and via immunomodulation potentials. Recent evidence also suggests that some plants and its components have shown promising antiviral properties against SARS-CoV-2. This review summarizes certain phytochemical agents along with their mode of actions and potential antiviral activities against important viral pathogens. A special focus has been given on medicinal plants and their extracts as well as herbs which have shown promising results to combat SARS-CoV-2 infection and can be useful in treating patients with COVID-19 as alternatives for treatment under phytotherapy approaches during this devastating pandemic situation. 2021 by the authors. Licensee MDPI, Basel, Switzerland. -
Medicinal potential of the Cape-pondweed family (Aponogetonaceae): A review
Aponogeton (Aponogetonaceae) is an aquatic genus comprising 60 species distributed in tropical and subtropical regions of the Old World. The species of the genus are traditionally used to treat a wide variety of diseases including cuts and wounds, stomach disorders and reviving digestive system, fungal infections, cough, tuberculosis, acne, cancer, diarrhea, dysentery, jaundice, snake bite, etc. A total of 50 compounds have been isolated from Aponogeton species. Essential oils, fatty acids and waxes, ester, quinones, steroids, terpenes and terpenoids, phenols and phenolics are the important compounds present in this genus. In this review, we provide an overview of the taxonomy, molecular phylogeny, biogeography, traditional medicinal uses, phytochemistry, pharmacological activities and tissue culture of Aponogeton. Other aspects such as the use of some species as model plant for studying programmed cell death (PCD) are also discussed. This review on the medicinal potential of the genus aims at attracting the attention of biologists to this phytochemically less explored plant group. The knowledge gaps in different areas of research and future perspectives are also discussed. 2022 SAAB -
MediCrypt: A Model with Symmetric Encryption for Blockchain Enabled Healthcare Data Protection
In the dynamic field of medicine, combining blockchain technology and data security becomes a vital strategy to solve the problem of protecting sensitive medical data. This study presents a new way to improve the security and privacy of medical data, using MediCrypt as an example of two- way encryption. Doctors initially used algorithms like AES or Blowfish to retrieve medical data. Smart contracts on the Ethereum-based blockchain introduce a layer of protection, combining SHA-256 with symmetric encryption technology. The multi-level transmission model includes encryption time, encryption time, elapsed time, and encryption size. Functionality in this model involves managing patient records (EHR), counterfeit drugs, drug reviews, clinical outcomes, and consent for all care areas. As shown in the methodology, the user ecosystem facilitates the exchange of information by defining the roles and responsibilities of doctors/pharmacists, administrators, and patients. The study shows the deployment of the MediCrypt model in three distinct stages. Distinct comparison of encryption time is done for different encryption algorithms. Also, parameters of MediCrypt model is compared with existing healthcare based blockchain models. 2024 IEEE. -
Meditating in VR
This chapter examines how immersion in virtual reality (VR) affects the psychological well-being, perceived interactivity, and positive thinking of young adults. Using a questionnaire adapted from Katy Tcha-Tokey's VR survey and established scales by Sally J. McMillan, Jang-Sun Hwang, and Diener, data was collected from 224 students at Christ University. Participants engaged in a VR meditation session using Meta Quest 2 headsets. Results indicated stronger correlations between immersion and psychological well-being (r = 0.511) and positive thinking (r = 0.485) compared to perceived interactivity (r = 0.319). Regression analyses confirmed immersion's predictive power for psychological well-being (? = 0.511, R2 = 0.261) and perceived interactivity (? = 0.485, R2 = 0.236), with lesser impact on positive thinking (R2 = 0.101). The study suggests that VR immersion notably influences psychological well-being and perceived interactivity among young adults. 2026 Scrivener Publishing LLC. -
Melamine derived N-doped Carbon nanotubes: A durable catalyst support for Pt nanoparticles in proton exchange membrane fuel cell
A cost-effective thermal pyrolysis route was adopted to synthesize N-doped carbon nanotube (NCNT) in a single step with the aid of melamine (carbon and nitrogen source) and cobalt catalyzed growth for the formation of N-doped carbon nanotubes. The NCNT was acid treated (fNCNT) to remove the metallic Co from the CNT which was elucidated using X-ray diffraction. Even though these noble metal-free materials are explored as Oxygen reduction reaction (ORR) electrocatalyst, for it to be employed in actual fuel cell the cathode requires noble metals such as Platinum (Pt) nanoparticles to improve its sluggish kinetics. Thus, this study is mainly focused on employing fNCNT as catalyst support in PEMFC, wherein the electrocatalyst was synthesized using microwave-assisted polyol method to decorate Pt nanoparticles on fNCNT, demonstrating its excellent durability of 32% electrochemical active surface area (ECSA) loss when subjected to standard protocols, and full cell performance of hybrid ((Pt/fNCNT) + CB) 412 mW cm?2 (better than commercial Pt/C) when deployed as electrocatalyst for ORR in Polymer electrolyte membrane (PEM) fuel cell, thus our findings open new avenues to explore, design and develop N-doped carbon nanotubes as durable catalyst for fuel cells. Graphical abstract: (Figure presented.) The Author(s), under exclusive licence to Springer Nature B.V. 2024. -
Melamine derived N-doped Carbon nanotubes: A durable catalyst support for Pt nanoparticles in proton exchange membrane fuel cell
A cost-effective thermal pyrolysis route was adopted to synthesize N-doped carbon nanotube (NCNT) in a single step with the aid of melamine (carbon and nitrogen source) and cobalt catalyzed growth for the formation of N-doped carbon nanotubes. The NCNT was acid treated (fNCNT) to remove the metallic Co from the CNT which was elucidated using X-ray diffraction. Even though these noble metal-free materials are explored as Oxygen reduction reaction (ORR) electrocatalyst, for it to be employed in actual fuel cell the cathode requires noble metals such as Platinum (Pt) nanoparticles to improve its sluggish kinetics. Thus, this study is mainly focused on employing fNCNT as catalyst support in PEMFC, wherein the electrocatalyst was synthesized using microwave-assisted polyol method to decorate Pt nanoparticles on fNCNT, demonstrating its excellent durability of 32% electrochemical active surface area (ECSA) loss when subjected to standard protocols, and full cell performance of hybrid ((Pt/fNCNT) + CB) 412 mW cm?2 (better than commercial Pt/C) when deployed as electrocatalyst for ORR in Polymer electrolyte membrane (PEM) fuel cell, thus our findings open new avenues to explore, design and develop N-doped carbon nanotubes as durable catalyst for fuel cells. The Author(s), under exclusive licence to Springer Nature B.V. 2024. -
Melanoma Skin Cancer Detection using a CNN-Regularized Extreme Learning Machine (RELM) based Model
Recent years have brought a heightened awareness of skin cancer as a potentially fatal type of human disease. While all three forms of skin cancer - Melanoma, Basal, and Squamous are terrifying, Melanoma is the most erratic. Melanoma cancer is curable if caught at an early stage. Multiple current systems have demonstrated that computer vision can play a significant role in medical image diagnosis. This study suggests a new approach to picture categorization that can help convolutional neural networks train more quickly (CNN). CNN has seen widespread use in multiclass image classification datasets, but its poor learning performance for huge volumes of data has limited its usefulness. On the other hand, whereas Regularized Extreme Learning Machine (RELM) are capable of rapid learning and have strong generalizability to improve their recognized accuracy quickly. This study introduces a novel CNN-RELM, a novel classifier that integrates convolutional neural networks with regularized extreme learning machines. CNN-RELM begins by training a Convolutional Neural Network (CNN) through the gradient descent technique until the desired learning and target accuracy is achieved. This approach outperforms the CNN and RELM model with an accuracy of around 98.6%. 2023 IEEE. -
Melatonin priming confers chromium tolerance in spinach (Spinacia oleracea) seedlings and field-grown plants
Heavy metal contamination of soils poses a significant risk to food safety by accumulating toxic metals in edible crops, such as leafy vegetables. This study tested whether melatonin seed priming reduces chromium accumulation while maintaining plant performance in Spinacia oleracea cultivar Arka Anupama under controlled and polyhouse conditions. Melatonin priming improved seedling growth under chromium stress, with 50-micromolar melatonin treated plants showing better performance. Under polyhouse conditions, 50 micromolar melatonin increased leaf number to 5.25 0.55 compared with 3.75 0.29 in chromium-stressed plants (40% increase), and improved leaf area to 3.70 0.35 cm2 in 100 micromolar melatonin-treated plants compared with 2.27 0.03 cm2 in chromium-stressed plants (63% increase). The chlorophyll normalized difference vegetation index increased from 0.15 0.04 in chromium-stressed plants to 0.26 0.01 in 50 micromolar melatonin-primed plants, representing approximately 78% improvement (significant p <.05). Atomic absorption spectroscopy analysis showed a 42.9% reduction in leaf chromium content following 50-micromolar treatment. Spectral analysis revealed stress-associated variations, including a 512515 cm?1 band under chromium stress. These findings indicate that melatonin priming improves plant growth and reduces chromium accumulation in spinach, with 50 micromolar showing the most consistent response. 2026 Taylor & Francis Group, LLC.