AI Medical Compendium

Deep Learning-Based Image Analysis Model for Classification and Quantification of Multiple Histopathological Findings in Rat Testis and Epididymis.

Toxicologic pathology Apr 5, 2026

Supervised deep learning-based image analysis models using whole slide images (WSIs) have been reported to be effective for detecting simple histopathological findings in laboratory animals. However, there are no models that simultaneously detect mul... read more

Artificial Intelligence-Based Perioperative Risk Assessment for Elderly Patients Undergoing Inguinal Hernia Repair in a Resource-Limited Setting.

World journal of surgery Apr 5, 2026

[Simulated consciousness, pseudo-empathy and the illusion of attachment: what can psychiatry do with artificial intelligence?].

Orvosi hetilap Apr 5, 2026

Over the past decade, the burden of mental disorders has grown while services remain capacity-constrained, pushing generative artificial intelligence toward psychiatric practice. This narrative review outlines how large language and multimodal models... read more

Deep learning-enhanced data-driven gating improves FDG PET/CT clinical image quality.

EJNMMI physics Apr 5, 2026

Quantum-inspired fused explainable deep learning framework for early enamel caries classification in intraoral photographs.

Odontology Apr 5, 2026

The visual detection of early enamel caries in intraoral photographs is challenging due to subtle lesion appearance and diagnostic subjectivity. This study aimed to develop and validate an explainable, quantum-simulated deep learning framework for th... read more

Integrative multi-omics identifies a diagnostic T cell signature for cutaneous squamous cell carcinoma.

Naunyn-Schmiedeberg's archives of pharmacology Apr 5, 2026

Cutaneous squamous cell carcinoma (cSCC) involves complex immune interactions. This study aimed to identify a T cell-related gene signature to characterize the immune landscape and aid in molecular diagnosis. We integrated single-cell RNA sequencing ... read more

Integration of multi-omics and machine learning to identify core genes in PANoptosisof lung adenocarcinoma and their mechanisms in the tumor microenvironment and therapeutic potential.

Naunyn-Schmiedeberg's archives of pharmacology Apr 5, 2026

Lung adenocarcinoma (LUAD) is one of the leading causes of cancer-related deaths worldwide, and its complex tumor microenvironment (TME) is a key barrier to treatment. PANoptosis is a novel programmed cell death mechanism that integrates features of ... read more

Construction of chronic inflammation and mitochondrial energy metabolism-associated predictive and therapeutic models for lung adenocarcinoma patients.

Discover oncology Apr 5, 2026

Predictive neuroimaging biomarkers of major depressive disorder treatment response: An umbrella review.

Psychiatry and clinical neurosciences Apr 5, 2026

Major depressive disorder (MDD) is a heterogeneous condition with varied responses to pharmacological, psychotherapeutic, and neuromodulation interventions. Identifying neuroimaging biomarkers predictive of treatment response could facilitate persona... read more

Identification of potential inhibitors of 3‑mercaptopyruvate sulfurtransferase with a deep-learning based screening of natural products.

Journal of computer-aided molecular design Apr 4, 2026

3-Mercaptopyruvate sulfurtransferase (3-MST), a key enzyme in sulfur metabolism, has recently gained attention as a potential anticancer target. However, reported 3-MST inhibitors remain limited, motivating the exploration of new scaffolds such as na... read more

Artificial Intelligence Medical Compendium