Artificial Intelligence Medical Compendium

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

Showing 6,751 to 6,760 of 205,891 articles

Bridging Acoustic and Semantic Spaces for Interpretable Voice Scoring via Zero-Shot Semantic Expansion

medRxiv
Subjective auditory-perceptual evaluation and uninterpretable deep learning models limit the clinical assessment of voice disorders. This study proposes a two-phase zero-shot framework to evaluate voice pathology. First, an Audio Spectrogram Transfor... read more 

Reliability and Concurrent Validity of a Computer Vision-Based Tool for Quantitative Finger Movement Analysis

medRxiv
Background: Accurate evaluation of fine motor abilities is a key aspect of neurological rehabilitation. However, conventional approaches like goniometry are limited by variations among raters and their difficulty in detecting active movement. On the ... read more 

Case-level artificial intelligence for multi-photo teledermatology submissions: development and internal validation using patient-submitted dermatology images

medRxiv
Background: Store-and-forward teledermatology commonly relies on several patient-submitted photographs of the same concern, but most dermatology artificial intelligence models classify single images independently. Objective: To develop and internally... read more 

Real-world impact of a sepsis early detection model integrated into clinical workflow: a quasi-experimental study

medRxiv
Background: Sepsis is a life-threatening condition in which delayed recognition and treatment are associated with increased mortality. While predictive models such as Epic's Early Detection of Sepsis Model (ESM) were developed to support early interv... read more 

Mesoscopic cortical activities associated with pupil-linked perceptions inferred via explainable machine learning

bioRxiv
Pupil dilation reflects arousal-related neural processes and is closely linked to sensory perception, attention, and cognitive state, but the mesoscopic cortical dynamics that accompany stimulus-evoked dilation remain unclear. Here, we combined simul... read more 

Trustworthy ML/AI for Aging Clocks: Preventing Systematic Prediction Bias in Biological Age Estimation

bioRxiv
Machine learning (ML)- and artificial intelligence (AI)-based aging clocks are increasingly used to quantify physiological and molecular aging from omics and medical imaging data as distinct from chronological age. Here, we characterize a fundamental... read more 

Neural networks learn forward dynamics when freed from numerical integration

bioRxiv
Seamless interaction between humans and machines requires interfaces that remain robust to the variability inherent in biological signals and physical environments. Advanced human-machine interfaces (HMIs) increasingly rely on machine learning to pre... read more 

A Foundation Model for the Cancer Genome

bioRxiv
Cancer is a disease of the genome, in which somatic mutations and copy-number alterations determine tumour identity, clinical behaviour, and response to therapy. Consortium-scale sequencing has profiled hundreds of thousands of tumours, yet clinical ... read more 

Ultra-efficient High Resolution 3D Reconstruction of Spatial Omics Data with Neural Transcriptomic Field

bioRxiv
Biological tissues are inherently three-dimensional (3D) ecosystems where spatial architecture dictates cellular function. While spatial omics technologies have revolutionized molecular profiling, they are largely restricted to isolated two-dimension... read more 

Eyewire II - A connectomic resource for resolving cell types and circuits of the mouse retina

bioRxiv
Comprehensive wiring diagrams from electron microscopy (EM) are a powerful tool to understand the inner workings of the brain. The retina is an easily accessible part of the brain that performs complex visual computations. Its thin, layered structure... read more