Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 49,581 to 49,590 of 224,513 articles

Comparing Modelling Architectures in the context of EGFR Status Classification in Non Small Cell Lung Cancer

medRxiv
Radiogenomics enables the non invasive characterisation of the genomic and molecular properties of tumours, with epidermal growth factor receptor (EGFR) mutations in non small cell lung cancer (NSCLC) being one of the most investigated applications. ... read more 

RED RHD (Rice Early Detection for Rheumatic Heart Disease): AI-Based Adaptive Multi-Regional System for Early Detection and Murmur Classification of Rheumatic Heart Disease

medRxiv
This study presents RED RHD, a machine learning methodology for early detection and classification of Rheumatic Heart Disease (RHD) using heart sound recordings. By leveraging OpenL3 deep acoustic embeddings, cloud-based workflows, and an ensemble of... read more 

A 'Silent Trial' Assessing the Accuracy of Large Language Models for Assisting Community Health Workers in Low-Resource Settings

medRxiv
Community health workers (CHWs) in low-resource settings deliver variable-quality care. This study used OpenAI's o3 and Google's Gemini Flash 2.5 to evaluate whether large language models (LLMs) 'listening' to CHW-patient interactions could generate ... read more 

Collaborative large language models (LLMs) are all you need for screening in systematic reviews

medRxiv
Background: The ability of large language models (LLMs) to work collaboratively and screen studies in a systematic review (SR) is under-explored. Hence, we aimed to evaluate the effectiveness of LLMs in automating the process of screening in systemat... read more 

Automated AI image recognition tools improve the efficiency of aerial wildlife counts: A multi-species case study on breeding seabirds and pinnipeds at the sub-Antarctic Bounty Islands.

bioRxiv
Accurate monitoring of populations is essential for conservation management, including for vulnerable seabirds. Yet traditional ground-based surveys are logistically challenging and time-consuming, especially in remote environments such as the sub-An... read more 

Evaluating Single-Cell Perturbation Response Models Is Far from Straightforward

bioRxiv
Predicting cellular responses to genetic and chemical perturbations remains a central challenge in single-cell biology and a key step toward building in silico virtual cells. The rapid growth of perturbation datasets and advances in deep-learning mod... read more 

Fast-cWDM Brain MRI: Fast Conditional Wavelet Diffusion Model for Synthesis Brain MRI Modality

bioRxiv
In this paper, we present a novel and efficient framework for cross-modality medical image synthesis, developed for BraSyn-Task 8. Our method combines the fast-sampling capabilities of the Fast-Denoising Diffusion Probabilistic Model (Fast-DDPM) with... read more 

Wavelet-Domain Multi-Representation and Ensemble Learning for Automated ECG Analysis

bioRxiv
Accurate diagnosis of cardiac abnormalities from electrocardiogram signals remains a central challenge in automated cardiovascular assessment. This study investigates the efficiency of time-frequency representations and deep learning architectures in... read more 

A Pan-Cancer Ex Vivo Drug Screen Atlas for Functional Precision Oncology

bioRxiv
Compared to immortalized cell lines, patient-derived organoids and other ex vivo models have been shown to better recapitulate patient responses to therapy. High cost and technical complexity have prevented the creation of pan-cancer ex vivo datasets... read more 

RNAiSpline: A Deep learning model for siRNA efficacy prediction

bioRxiv
RNA interference (RNAi) is a crucial biological post-transcriptional gene silencing mechanism where small interfering RNA (siRNA) guides RNA-induced silencing complex (RISC) to bind with messenger RNA (mRNA) thereby silencing it and stopping protein ... read more