Artificial Intelligence Medical Compendium

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

Showing 32,141 to 32,150 of 220,797 articles

[Annual advances in clinical applications of pulmonary function testing 2025].

Zhonghua jie he he hu xi za zhi = Zhonghua jiehe he huxi zazhi = Chinese journal of tuberculosis and respiratory diseases
This review systematically synthesizes and critically appraises domestic and international advances in pulmonary function tests (PFT) research and clinical applications between October 2024 and September 2025. Three major Chinese guidelines or expert... read more 

[Annual progress in imaging diagnosis of tuberculosis in 2025].

Zhonghua jie he he hu xi za zhi = Zhonghua jiehe he huxi zazhi = Chinese journal of tuberculosis and respiratory diseases
Tuberculosis (TB) remains a major global public health threat and continues to be one of the leading causes of death from infectious diseases worldwide. Achieving the 2030 goal of"Ending TB"depends critically on the early and precise diagnosis of TB.... read more 

Actinic keratosis staging in multimodal image data.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Actinic Keratosis (AK) is a common skin condition, usually appearing on sun-exposed areas, whose progression is associated with characteristic dermatoscopic and structural changes. Early detection of AK is crucial, as cancer... read more 

Fair enough? How developers and clinicians justify who receives physical assistive robotics in rehabilitation.

Social science & medicine (1982)
BACKGROUND: Physical assistive robots are increasingly promoted in rehabilitation. However, it remains unclear how and for whom, physical assistive robots move from laboratory prototypes into rehabilitation practice, and whether this transition mitig... read more 

Salivary biomarkers and their diagnostic importance in oral diseases.

Archives of oral biology
OBJECTIVE: This review critically evaluates the diagnostic potential of salivary biomarkers in oral diseases, highlighting their role as non-invasive tools for early detection, disease monitoring, and precision oral healthcare. DESIGN: A narrative re... read more 

Interpretable machine learning and molecular simulations identify natural pancreatic lipase inhibitors and hydrophobic hotspot residues.

Bioorganic chemistry
Pancreatic lipase (PL) is a validated peripheral target for limiting dietary fat absorption, yet structurally diverse natural inhibitors remain scarce. We assembled a PL inhibitor dataset from public resources and trained a random-forest classifier u... read more 

Geo-Mamba: Geometry-informed state-space learning of functional brain organization.

Medical image analysis
Functional magnetic resonance imaging (fMRI) derived functional connectivity (FC) is represented as graphs and as correlation or covariance matrices that live on non-Euclidean spaces, cortical graphs and the Riemannian manifold of symmetric positive-... read more 

Free water in the hippocampal cingulum as a Radiomic biomarker for Identifying inflammatory neuropsychiatric Lupus: A cross-sectional case-control study.

Journal of autoimmunity
PURPOSE: Neuropsychiatric systemic lupus erythematosus (NPSLE) is a serious manifestation of systemic lupus erythematosus (SLE), yet its neuroimaging diagnosis remains challenging. This study aims to explore the value of FW-corrected diffusion model ... read more 

A machine learning approach to predicting dyspnea with noninvasive biomarkers.

Respiratory physiology & neurobiology
Dyspnea is the subjective sensation of breathing discomfort. This symptom is highly prevalent in patients with chronic and critical illness, and its presence is associated with poor clinical outcomes and long-term psychological trauma. The multidimen... read more 

Towards transparent and interpretable screening: multi-biofluid FTIR spectroscopy with LLM-Augmented explainability for pancreatic cancer detection.

Methods (San Diego, Calif.)
Early detection of pancreatic cancer remains a critical challenge in oncology, with current diagnostic methods often failing to identify the disease until advanced stages. However, diagnostic accuracy alone may be insufficient for clinical adoption a... read more