Artificial Intelligence Medical Compendium

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

Showing 411 to 420 of 234,501 articles

National incidence of coccidioidomycosis in the United States estimated through machine learning integration of epidemiological, veterinary, and socioecological data

medRxiv
Importance: Coccidioidomycosis, also known as Valley fever, is a serious fungal disease caused by inhaling Coccidioides spores aerosolized from the soil. Despite rising public health concern, the distribution and incidence of coccidioidomycosis in th... read more 

BanglaDiaHallu: Hallucinations of large language models and the effect of guideline-grounded retrieval-augmented generation in Bangla diabetes question answering

medRxiv
Large language models (LLMs) are increasingly consulted for health advice, but they can produce fluent statements that are false or unsupported, known as hallucinations, and this risk is poorly characterised in low-resource languages such as Bangla. ... read more 

Decoding Clade-Specific bNAb-HIV-1 Env Interactions Using Machine Learning

bioRxiv
Human immunodeficiency virus type 1 (HIV-1) exhibits extensive genetic diversity, posing a major challenge to AIDS vaccine development. Broadly neutralizing antibodies (bNAbs) isolated from HIV-1-infected individuals offer valuable templates for desi... read more 

Decoding plant x environment interactions through spatial gradients in leaf physiology and metabolism

bioRxiv
Succulent leaves are well known to combine photosynthesis, carbon storage and hydraulic buffering. However, their metabolic responses to heat and drought may differ along the same leaf axis. We investigated spatial and temporal changes in leaf tissue... read more 

RePurpose: An LLM-Assisted, Source-Traceable Drug Repurposing Tool with Retrospective Validation on Clemastine in Multiple Sclerosis

bioRxiv
Summary Thus far, evidence for drug repurposing is contained in target-, drug-, trial-, and literature-based data sources that are challenging to synthesize for non-specialists. Here, we introduce RePurpose, a web-based tool that takes as input a top... read more 

Facilitating Valid Statistical Inference in Biomedical Image Synthesis

bioRxiv
Generative AI for medical image synthesis is increasingly used to impute missing data and augment biomedical datasets. Yet despite achieving high computational similarity to their real-world counterparts, synthetic images remain uncommon in clinical ... read more 

Two Pleckstrin homology domains scaffold SNAP-47-containing SNARE complexes

bioRxiv
Long-term potentiation requires the regulated insertion of AMPA receptors into the postsynaptic membrane of neurons, a process mediated by a SNARE complex containing SNAP-47, syntaxin-3, and synaptobrevin-2. Compared to other SNAP proteins, SNAP-47 e... read more 

A relational architecture of the human genome

bioRxiv
Complex systems exhibit organization not only through their components but also via their interdependencies. Local nucleotide dependencies underpin regulatory motifs and RNA structures, yet principles governing a higher-order organization across the ... read more 

Evaluation and primer for using DeepLabCut to track small animals in large spaces

bioRxiv
DeepLabCut (DLC), a machine learning-based pose estimation tool, has dramatically increased the throughput of behavioral tracking. Yet its implication remains limited by lack of validation data from diverse scenarios and users' unfamiliarity with the... read more 

Understanding Performance Plateaus and Representation Collapse in 3D MRI Transformers Trained to Classify Brain Disease

bioRxiv
In medical imaging AI, we commonly assume that diagnostic classifiers will increase in accuracy if they are trained on more data, but in reality, their performance often plateaus. To understand this behavior, we ran a spectral analysis of 3D vision t... read more