AI Medical Compendium

Deep learning assisted particle size ranking and estimation from SEM images without explicit segmentation.

Micron (Oxford, England : 1993) Mar 26, 2026

In nanomaterial research, accurate determination of particle size and morphology from Scanning Electron Microscopy (SEM) images is a fundamental requirement. Conventional approaches predominantly rely on explicit segmentation, which necessitates labo... read more

Artificial intelligence-assisted FTIR spectroscopy for hormone receptor subtyping in formalin-fixed breast Cancer tissues.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Mar 26, 2026

BACKGROUND: Determination of estrogen receptor (ER) and progesterone receptor (PR) status is critical for breast cancer subtyping and guiding endocrine therapy. Although immunohistochemistry (IHC) remains the diagnostic gold standard, it is costly, l... read more

Calibration-free on-site detection of microcystin-LR using integrated biosensing, multi-parameter water quality monitoring, and machine learning.

Water research Mar 26, 2026

Microcystin-lysine-arginine (MC-LR) is a potent hepatotoxic cyanotoxin produced during harmful algal blooms and is recognized as a global environmental concern due to its widespread occurrence in surface waters. Screen-printed carbon electrode (SPCE)... read more

PCTPS: Accurate prediction of phase-separated proteins using protein language model embeddings and a CTN-KAN framework.

Journal of molecular graphics & modelling Mar 26, 2026

Phase-separated proteins play a critical role in understanding cellular mechanisms and functions. However, developing accurate and efficient computational methods for predicting phase-separated proteins remains challenging. Existing methods often rel... read more

A machine learning approach using echocardiographic and hematological parameters to classify cerebral small vessel disease burden.

Clinical neurology and neurosurgery Mar 26, 2026

BACKGROUND: Cerebral small vessel disease (CSVD) is a leading cause of stroke and dementia and is associated with cardiac and hematological biomarkers. Although brain magnetic resonance imaging (MRI) remains the reference standard for assessing CSVD ... read more

Agentic AI in rheumatology.

The Lancet. Rheumatology Mar 26, 2026

Large language models have generated intense interest in clinical artificial intelligence (AI), yet their evolution from passive chatbots into agentic systems capable of autonomous planning, tool use, and multistep execution represents a distinct tec... read more

Leveraging artificial intelligence to personalize treatment for eating disorders: A proof-of-concept study.

Journal of affective disorders Mar 26, 2026

Eating disorders are complex conditions with high relapse and mortality rates, and fewer than half of adults achieve clinically significant improvement with current evidence-based treatments. Personalized approaches using idiographic, data-driven mon... read more

Silence Kills 2.0: How Communication Failures Stifle Innovation and Harm Patients.

American journal of critical care : an official publication, American Association of Critical-Care Nurses Mar 26, 2026

BACKGROUND: In health care organizations in which silence is the norm, questionable competence, rule-breaking, and mistakes ("crucial moments") often persist, putting patients and clinicians at risk. Silence may also impede an organization's behavior... read more

The Bitter Lesson and its Implications for Surgical Artificial Intelligence.

Annals of surgery Mar 26, 2026

Machine learning predicts hepatocellular carcinoma risk from routine clinical data: a large population-based multicentric study.

Cancer discovery Mar 26, 2026

Hepatocellular carcinoma (HCC) is a highly fatal tumor, for which risk stratification is crucial, yet remains challenging. Here, we develop an interpretable machine-learning framework for HCC risk stratification based on routinely collected clinical ... read more

Artificial Intelligence Medical Compendium