T R Mahesh
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View article: Optimizing language model fine-tuning and quantization for enhanced medical question answering
Optimizing language model fine-tuning and quantization for enhanced medical question answering Open
This paper introduces an end-to-end fine-tuning and compression solution for the EleutherAI GPT-Neo 125 M language model. It employs a new optimization procedure that boosts the performance of the model in the task of medical question answ…
View article: EPCO-60. FOUNDATIONAL MODEL FOR VIRTUAL EXPERIMENTAL FRAMEWORK (VEF) FOR BIOMEDICAL APPLICATIONS PREDICTS MASTER REGULATORS IN HUMAN GLIOBLASTOMA
EPCO-60. FOUNDATIONAL MODEL FOR VIRTUAL EXPERIMENTAL FRAMEWORK (VEF) FOR BIOMEDICAL APPLICATIONS PREDICTS MASTER REGULATORS IN HUMAN GLIOBLASTOMA Open
BACKGROUND Mapping causal effects of genetic perturbations is hampered by the combinatorial complexity of multigene interactions and the limits of wet-lab screens. Current deep-learning methods treat perturbations as binary, ignore dosage …
View article: QBrainNet: harnessing enhanced quantum intelligence for advanced brain stroke prediction from medical imaging
QBrainNet: harnessing enhanced quantum intelligence for advanced brain stroke prediction from medical imaging Open
Introduction Brain stroke is still one of the leading causes of death and long-term disability in the world. Early and correct diagnosis is therefore important for patient outcome. Although Convolution Neural Network (CNN), classical machi…
View article: Correction: Automated classification and explainable AI analysis of lung cancer stages using EfficientNet and gradient-weighted class activation mapping
Correction: Automated classification and explainable AI analysis of lung cancer stages using EfficientNet and gradient-weighted class activation mapping Open
[This corrects the article DOI: 10.3389/fmed.2025.1625183.].
View article: Image integrity and tampering detection: A hybrid approach to copy-paste forgery detection using ORB-SSD and CNN
Image integrity and tampering detection: A hybrid approach to copy-paste forgery detection using ORB-SSD and CNN Open
Digital image manipulation, especially copy-paste forgery, presents significant challenges to maintaining the authenticity and credibility of visual content in the digital age. As image editing techniques become increasingly sophisticated,…
View article: PneumoNet: Deep Neural Network for Advanced Pneumonia Detection
PneumoNet: Deep Neural Network for Advanced Pneumonia Detection Open
Background: Advancements in computational methods in medicine have brought about extensive improvement in the diagnosis of illness, with machine learning models such as Convolutional Neural Networks leading the charge. This work introduces…
View article: Automated classification and explainable AI analysis of lung cancer stages using EfficientNet and gradient-weighted class activation mapping
Automated classification and explainable AI analysis of lung cancer stages using EfficientNet and gradient-weighted class activation mapping Open
Precise classification of lung cancer stages based on CT images remains a significant challenge in oncology. This is vitally necessary for determining prognosis and creating practical treatment plans. Traditional methods mainly rely on hum…
View article: Corrigendum to: “Multi-view neutrosophic <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"><mml:mi>c</mml:mi></mml:math>-means clustering algorithms” [Expert Syst. Appl. 260 (2025) 126763]
Corrigendum to: “Multi-view neutrosophic -means clustering algorithms” [Expert Syst. Appl. 260 (2025) 126763] Open
View article: Enhanced household energy consumption forecasting using multivariate long short-term memory (LSTM) networks with weather data integration
Enhanced household energy consumption forecasting using multivariate long short-term memory (LSTM) networks with weather data integration Open
View article: An optimized domain-specific shrimp detection architecture integrating conditional GAN and weighted ensemble learning
An optimized domain-specific shrimp detection architecture integrating conditional GAN and weighted ensemble learning Open
Deep learning primarily operates on images which contain hidden patterns that are quantified through pixel intensities. Deep learning is used to analyze the image patterns and to recognize the objects. The detection process includes the cr…
View article: Refining digital security with EfficientNetV2-B2 deepfake detection techniques
Refining digital security with EfficientNetV2-B2 deepfake detection techniques Open
View article: Mitigating class imbalance in churn prediction with ensemble methods and SMOTE
Mitigating class imbalance in churn prediction with ensemble methods and SMOTE Open
This study examines how imbalanced datasets affect the accuracy of machine learning models, especially in predictive analytics applications such as churn prediction. When datasets are skewed towards the majority class, it can lead to biase…
View article: A Novel Ensemble Empirical Decomposition and Time–Frequency Analysis Approach for Vibroarthrographic Signal Processing
A Novel Ensemble Empirical Decomposition and Time–Frequency Analysis Approach for Vibroarthrographic Signal Processing Open
Signal processing techniques play a critical role in addressing real-world applications across domains such as sensor analysis, defence, and clinical and biomedical fields. Within healthcare, computer-aided diagnostic (CAD) systems have be…
View article: Enhanced tuberculosis detection using Vision Transformers and explainable AI with a Grad-CAM approach on chest X-rays
Enhanced tuberculosis detection using Vision Transformers and explainable AI with a Grad-CAM approach on chest X-rays Open
View article: Thermal Breast Cancer Detection Using Deep Learning and Grad-CAM Visualization
Thermal Breast Cancer Detection Using Deep Learning and Grad-CAM Visualization Open
This paper presents a robust deep learning framework for thermal breast cancer detection using grayscale thermal images. Leveraging a pre-trained VGG16 model, we classify images into 'normal' and 'abnormal' categories, integrating data aug…
View article: Integration of focused ultrasound and dynamic imaging control system for targeted neuro-modulation
Integration of focused ultrasound and dynamic imaging control system for targeted neuro-modulation Open
Clinical trials using standard datasets of fMRI and NIRS have proved that the approach improved targeting accuracy by ∼18 %, reduced off-target effects by ∼55 % and enhanced therapeutic outcomes by 50 % over current methods, suggesting its…
View article: Machine learning-driven intelligent water quality assessment for enhanced drinking safety and real-time consumer awareness
Machine learning-driven intelligent water quality assessment for enhanced drinking safety and real-time consumer awareness Open
As to the sphere of smart water management and managing water Internet of Things (IoT) systems, water condition safety for drinking is very important. The proposed methodology, known as the Smart Water Consumption Monitoring System (SWCMS)…
View article: Spiking Neural Dynamics and Federated Routing for Ultralow‐Latency in 6G Industry 5.0
Spiking Neural Dynamics and Federated Routing for Ultralow‐Latency in 6G Industry 5.0 Open
The implementation of advanced communication technologies with intelligent systems under Industry 5.0 demands ultralow‐latency 6G networks to support seamless human–machine connections. This study introduces SNN optimization for low‐latenc…
View article: Applying Digital Twin Technology in Smart Manufacturing with Human-Robot Interaction Using Convolutional Neural Network
Applying Digital Twin Technology in Smart Manufacturing with Human-Robot Interaction Using Convolutional Neural Network Open
View article: DeepFake Detection: Evaluating the Performance of EfficientNetV2‐B2 on Real vs. Fake Image Classification
DeepFake Detection: Evaluating the Performance of EfficientNetV2‐B2 on Real vs. Fake Image Classification Open
The surge in digitally altered images has necessitated advanced solutions for reliable image verification, impacting sectors from media to cybersecurity. This work provides an effective method of real vs. deepfake image distinction through…
View article: Enhancing drug discovery and patient care through advanced analytics with the power of NLP and machine learning in pharmaceutical data interpretation
Enhancing drug discovery and patient care through advanced analytics with the power of NLP and machine learning in pharmaceutical data interpretation Open
This study delves into the transformative potential of Machine Learning (ML) and Natural Language Processing (NLP) within the pharmaceutical industry, spotlighting their significant impact on enhancing medical research methodologies and op…
View article: Optimizing Personalized and Context-Aware Recommendations in Pervasive Computing Environments
Optimizing Personalized and Context-Aware Recommendations in Pervasive Computing Environments Open
The researchers in the current era provided many new recommendation methodologies. Though various recommendation techniques exist, there is a need to develop a unique technique for capturing latent factors and patterns from sparse and high…
View article: AgriFusion: A Low‐Carbon Sustainable Computing Approach for Precision Agriculture Through Probabilistic Ensemble Crop Recommendation
AgriFusion: A Low‐Carbon Sustainable Computing Approach for Precision Agriculture Through Probabilistic Ensemble Crop Recommendation Open
Optimizing crop production is essential for sustainable agriculture and food security. This study presents the AgriFusion Model, an advanced ensemble‐based machine learning framework designed to enhance precision agriculture by offering hi…
View article: Enhancing image-based diagnosis of gastrointestinal tract diseases through deep learning with EfficientNet and advanced data augmentation techniques
Enhancing image-based diagnosis of gastrointestinal tract diseases through deep learning with EfficientNet and advanced data augmentation techniques Open
View article: Employing Xception convolutional neural network through high-precision MRI analysis for brain tumor diagnosis
Employing Xception convolutional neural network through high-precision MRI analysis for brain tumor diagnosis Open
The classification of brain tumors from medical imaging is pivotal for accurate medical diagnosis but remains challenging due to the intricate morphologies of tumors and the precision required. Existing methodologies, including manual MRI …
View article: Redefining retinal vessel segmentation: empowering advanced fundus image analysis with the potential of GANs
Redefining retinal vessel segmentation: empowering advanced fundus image analysis with the potential of GANs Open
Retinal vessel segmentation is a critical task in fundus image analysis, providing essential insights for diagnosing various retinal diseases. In recent years, deep learning (DL) techniques, particularly Generative Adversarial Networks (GA…
View article: Optimized polycystic ovarian disease prognosis and classification using AI based computational approaches on multi-modality data
Optimized polycystic ovarian disease prognosis and classification using AI based computational approaches on multi-modality data Open
View article: MResGat: Multi-head Residual Dilated Convolution Assisted Gated Unit Framework for Crop Yield Prediction
MResGat: Multi-head Residual Dilated Convolution Assisted Gated Unit Framework for Crop Yield Prediction Open
The importance of predicting crop yields has increased due to growing concerns of surrounding food security. Early forecasting of crop yields holds a pivotal role in avoiding starvations by estimating the food supply available for the expa…
View article: Enhancing visual seismocardiography in noisy environments with adaptive bidirectional filtering for Cardiac Health Monitoring
Enhancing visual seismocardiography in noisy environments with adaptive bidirectional filtering for Cardiac Health Monitoring Open
Our empirical tests demonstrate exceptional signal improvement with the application of our ABF approach. The accuracy in heart rate estimation reached an impressive r-squared value of 0.95 at - 20 dB SNR, significantly outperforming the ba…
View article: Revolutionizing breast ultrasound diagnostics with EfficientNet-B7 and Explainable AI
Revolutionizing breast ultrasound diagnostics with EfficientNet-B7 and Explainable AI Open
Breast cancer is a leading cause of mortality among women globally, necessitating precise classification of breast ultrasound images for early diagnosis and treatment. Traditional methods using CNN architectures such as VGG, ResNet, and De…