Pathology

Interpretable machine learning model for predicting hemorrhage following ultrasound-guided percutaneous renal biopsy: a multicenter study.

OBJECTIVE: This study aims to develop and validate an interpretable machine learning (ML) model for predicting post-procedural hemorrhage (PH) after ultrasound-guided percutaneous renal biopsy (PRB), aiding perioperative management. MATERIALS AND METHODS: A retrospective analysis was conducted using data from 664 patients to develop and internally validate the predictive model. Key ultrasound para...

Charting human organogenesis across the Carnegie stages from a whole-embryo perspective.

The Carnegie stages represent a critical window in human development, during which organ primordia emerge, tissue identities diversify, and many congenital disorders are thought to originate. However, this period has remained difficult to study at the whole-embryo scale. Recent advances in spatial and single-cell genomics are beginning to close this gap. This article discusses the significance of ...

Histopathology: An investigation so valuable but often neglected in orthopaedic infections.

The incidence of osteoarticular infections is steadily increasing, driven by rising road traffic injuries, greater longevity, increasing comorbidities...

The utility of artificial intelligence for DNA variant curation in the Mendelian genetic disorder familial hypercholesterolaemia.

The assessment of DNA sequence variants for biological function and their classification into risk categories is time-consuming. This has widened the ...

MR-AIV reveals in vivo brain-wide fluid flow with physics-informed AI.

The circulation of cerebrospinal and interstitial fluid plays a vital role in clearing metabolic waste from the brain, and its disruption has been lin...

Epigenetic precision diagnostics of traditional Chinese medicine (TCM) syndrome differentiation: a pilot study of atrial fibrillation with qi-yin deficiency syndrome based on 5-hydroxymethylcytosine signatures in extracellular vesicle DNA from plasma.

BACKGROUND: Syndrome differentiation in Traditional Chinese Medicine (TCM) is pivotal to clinical practice and dictates the efficacy of medicinal trea...

Multimodal Artificial Intelligence for Cardiac Amyloidosis Diagnosis: Integrating Echocardiography With Clinical and Laboratory Data for Improved Detection.

BACKGROUND: Cardiac amyloidosis (CA) is an underdiagnosed yet treatable cause of heart failure in which timely diagnosis is essential to initiate life...

Elucidating the molecular mechanisms linking bisphenol A to breast cancer: an integrated study of bioinformatics, machine learning, and molecular docking.

Bisphenol A (BPA) is a prevalent environmental endocrine disruptor linked to breast cancer. However, the precise molecular mechanisms and core therape...

Multimodal Prediction of Renal Tumor Malignancy From Radiology Reports and Structured Electronic Health Records: Retrospective Cohort Study.

BACKGROUND: Accurate preoperative prediction of renal tumor malignancy is critical for guiding decisions and reducing overtreatment, as a substantial ...

Labelling in cryogenic electron tomography - Bridging the gap between correlative light and electron microscopy and protein identification.

Cryogenic electron tomography (cryoET) offers unparalleled views into the molecular architecture of cells. As no stains or fixation are used, electron...

Multimodal Deep Learning for Benign vs Malignant Eyelid Lesion Classification Using Optical Coherence Tomography and Clinical Images.

PURPOSE: To evaluate the performance of deep learning models using optical coherence tomography (OCT) volumes, clinical photographs, and their multimo...

Interpretable machine learning model using peripheral blood for non-invasive detection of moderate-to-severe myelofibrosis in JAK2 V617F-positive MPNs: A multicentre pilot proof-of-concept study.

Progression to moderate-to-severe myelofibrosis (MF) in JAK2 V617F-positive myeloproliferative neoplasms (MPNs) is often clinically silent, and bone m...

[MRI-based deep learning model for preoperative prediction of urothelial carcinoma with variant histology of bladder: a retrospective, multicenter study].

Objectives: To develop a deep learning model based on magnetic resonance imaging (MRI) for the preoperative prediction of urothelial carcinoma with va...

Research on motor diagnosis and maintenance decision-making technology based on DCCNN-L transformer and fault knowledge graph.

Traditional deep learning methods for motor fault diagnosis have primarily focused on signal-based classification. Intelligent operation and maintenan...

Artificial Intelligence in Kidney Transplant Pathology: Current Evidence, Limitations, and Relevance to the Banff Framework.

The Banff Classification, established in 1991, provides a global standard for diagnosing and grading kidney transplant pathology, evolving through reg...

What Are Computer-Assisted Methods Achieving in Fine-Needle Aspiration Cytology of the Pancreas? A Systematic Review and Meta-Analysis.

OBJECTIVE: Pancreatic malignancies present major diagnostic challenges. The gold standard for diagnosis is endoscopic ultrasound-guided fine-needle as...

Comparison of systolic and diastolic CT-FFR for myocardial ischemia diagnosis.

BACKGROUND: CT-derived fractional flow reserve (CT-FFR) is a powerful tool for identifying hemodynamic ischemia. Coronary CT angiography (CCTA) images...

Decoding lactylation heterogeneity in glioblastoma: machine learning identifies G6PC3 as a prognostic target.

BACKGROUND: Glioblastoma (GBM) is the most common malignant glioma in adults. It has an extremely poor prognosis, highlighting an urgent need for new ...

A machine learning-based risk prediction framework for atypical hyperplasia and endometrial cancer in postmenopausal women.

BACKGROUND: This study aimed to develop and internally validate a machine learning-based model for predicting endometrial malignancy, defined as atypi...

Predicting neoadjuvant breast cancer therapy response using BRIDGE from tumor transcriptomics and histopathology.

BACKGROUND: While expression-based signatures inform adjuvant therapy in breast cancer (BC), no approved molecular biomarkers exist for the neoadjuvan...