Pathology

Explainable artificial intelligence reveals key surgical parameters in robot-assisted and open radical prostatectomy.

Preoperative risk stratification for radical prostatectomy is crucial, yet predicting the wide range of postoperative outcomes remains a significant challenge. While machine learning (ML) shows promise, "black box" models limit clinical translatability. This study aimed to predict postoperative parameters using ML and employ explainable AI (XAI) to identify their key clinical drivers. In a retrosp...

Systems pharmacology reveals type I interferon and myeloid-like B cell reprogramming as candidate druggable axes in antiphospholipid syndrome.

Antiphospholipid syndrome (APS) lacks disease-modifying targeted therapies, and its molecular heterogeneity remains poorly characterized. We employed an integrative systems pharmacology approach combining weighted gene co-expression network analysis (WGCNA), single-cell RNA sequencing, Connectivity Map (CMap) screening, and molecular docking to prioritize candidate therapeutic targets in APS. WGCN...

Bioinformatics and Machine-Learning Identification of Pulmonary Hypertension Biomarkers and Candidate Therapeutic Compounds.

This study aimed to identify pulmonary hypertension (PH)-associated molecular biomarkers and candidate small-molecule compounds using public transcrip...

[Advances in deep learning multimodal fusion for early diagnosis of knee osteoarthritis].

Knee osteoarthritis (KOA) is a common chronic degenerative disease that causes pain, functional limitation, and reduced quality of life in middle-aged...

Tissue-Agnostic Cellular Morphometric Biomarkers for Risk-Adapted Management Across Gastrointestinal Precancerous Lesions and Cancers.

While precision oncology increasingly adopts tissue-agnostic paradigms, current strategies remain heavily reliant on molecular alterations, with limit...

Edge-centric brain connectomes reveal two molecularly distinct neurobiological subtypes of adolescent major depressive disorder.

Adolescent major depressive disorder (MDD) is a heterogeneous disorder that complicates diagnosis and treatment. However, the mechanisms underlying th...

Radiolabeled drug-delivery and controlled-release nanocarriers for arthritis: Clinical evidence, kinetic modeling, radiation-safety challenges, and precision nanotheranostics.

BACKGROUND: Arthritis comprises a heterogeneous group of inflammatory and degenerative joint disorders characterized by distinct pathological mechanis...

Evaluation of the physical and radiological properties of different Fricke gel formulations as water-equivalent materials and biological tissues.

Fricke gel dosimeters, also known as hydrogels, have emerged as attractive tools in clinical dosimetry due to the requirements of quality assurance pr...

Diagnosis of Clinically Significant Prostate Cancer in Multiparametric MRI with Pseudo-Localization of Suspected Lesion.

To develop a two-stage diagnostic framework using pseudo-localization for patient-level diagnosis of clinically significant prostate cancer (csPCa) on...

Prediction of Lymph Node Metastasis in Early Gastric Cancer Using Foundation Model Ensembles and Patch-Based Histopathological Interpretation.

PURPOSE: Accurate prediction of lymph node metastasis (LNM) remains challenging in early gastric cancer (EGC), particularly when determining the need ...

Distinct relationships of compartment-specific fat distribution profiles with cardiovascular ageing and future cardiovascular events.

BACKGROUND: Obesity is a major contributor to cardiovascular disease (CVD). Different fat depots may have distinct effects on cardiac ageing and cardi...

Artificial Intelligence Detection of Interval Breast Cancers on False-negative Screening Mammograms: A Retrospective Lesion-level Analysis.

RATIONALE AND OBJECTIVES: Interval breast cancers (IBCs) occur after false-negative (FN) screening mammograms and can be diagnostically challenging. T...

Predicting Synchronous Liver Metastasis in Pancreatic Cancer Using CT Radiomics and Clinical Features: A Machine Learning Approach.

RATIONALE AND OBJECTIVES: To address the challenge of preoperative prediction of synchronous liver metastasis (LM) in pancreatic cancer (PC), we devel...

Predictive design of tissue-specific mammalian enhancers that function in the mouse embryo.

Enhancers control tissue-specific gene expression across animals1. Although deep learning2,3 has enabled enhancer prediction and design in mammalian c...

Multimodal Ultrasound-Based Decision Support for Bethesda IV Thyroid Nodules: Integration of Clinical, Radiomics, Deep Learning, and Topological Features.

To develop and internally validate a multimodal ultrasound-based decision support framework for benign-malignant risk stratification of Bethesda IV th...

The Imaging Compass: Navigating Reperfusion in Acute Ischemic Stroke.

The management of acute ischemic stroke has shifted from rigid time-based protocols to imaging-driven, tissue-based reperfusion strategies. Non-contra...

Developing and evaluating automated deep learning and human-in-the-loop vision-language systems for microplastic characterization.

Microplastic (MP) pollution poses escalating environmental risks, demanding efficient and reproducible tools for morphological characterization of pla...

Automated Deep Learning Protocol for Quantifying Cell Viability in Live/Dead Fluorescence Microscopy.

The assessment of live/dead cells by means of fluorescence microscopy is a standard technique for assessing cell viability but relies on manual counti...

Saliva Liquid Biopsy for Detection of Oral and Systemic Diseases.

Saliva has emerged as a compelling liquid biopsy for the non-invasive diagnosis and monitoring of both oral and systemic diseases. Secreted by major a...

Can Large Language Models Preserve Diagnostic Accuracy Despite Patient Self-Diagnosis and Framing Bias in Hypothetical Upper-Extremity Scenarios?

PURPOSE: Online health queries are often addressed by large language models (LLMs) embedded in search engines. It is possible that LLMs, like human cl...