Leukemia

Interpretable MRI-Based Machine Learning Model for Noninvasive Prediction of Axillary Lymph Node Metastasis After Neoadjuvant Chemotherapy in Breast Cancer.

RATIONALE AND OBJECTIVES: Accurate prediction of axillary lymph node metastasis (ALNM) after neoadjuvant chemotherapy (NAC) remains challenging in breast cancer. This study aimed to develop an interpretable machine learning model integrating MRI-based radiomics, deep learning features, and the Node-RADS score for noninvasive ALNM prediction after NAC. MATERIALS AND METHODS: In this multicenter ret...

Patient attitudes toward ambient artificial intelligence scribes in clinical care: insights from a cross-sectional study.

OBJECTIVE: To assess patient attitudes towards ambient artificial intelligence (AI) scribes, including comfort, trust, perceived impact on provider interactions, and willingness for future use, and to examine how sociodemographic, health factors, digital literacy, and privacy concerns shape attitudes. MATERIALS AND METHODS: We analyzed cross-sectional data from an online survey of 12 153 adults (5...

Genomics of kidney volumes: one size does not fit all.

To characterize the genetic basis of chronic kidney disease, genome-wide association studies focused on chronic kidney disease-defining traits that we...

COL14A1 drives ischemic cardiac injury in PCOS: an artificial intelligence-identified biomarker.

BACKGROUND: Polycystic ovary syndrome (PCOS) and ischemic cardiomyopathy (ICM) share metabolic and cardiovascular risk factors, including insulin resi...

Prediction of mortality, bleeding, and ischaemic events in patients with cancer and acute coronary syndrome: a model development and validation study.

BACKGROUND: Accurate assessment of mortality, bleeding, and atherothrombotic risk in patients with cancer and acute coronary syndrome could inform nov...

Emerging roles of artificial intelligence/machine learning (AI/ML) towards new understandings in molecular crosstalk between circRNA-CUL3-TKI to resensitize chemoresistant cancers.

Cancer arises and is resistant to therapy via intricate molecular networks that are poorly characterised. While individually, Cullin-3 (CUL3) and circ...

An interpretable machine learning model for predicting survival in pancreatic cancer via SHAP: a multicenter study.

BACKGROUND: Existing pancreatic cancer prediction models still have significant limitations until now. This multicenter retrospective study aimed to i...

Parameter-efficient fine-tuning enables scalable transfer of regulatory sequence models to novel contexts.

BACKGROUND: DNA sequence deep learning models can accurately predict epigenetic and transcriptional profiles, enabling analysis of gene regulation and...

μPharma: A microfluidic, AI-driven pharmacotyping platform for single-cell drug sensitivity prediction in leukemia.

BACKGROUND: Pharmacotyping, the ex vivo measurement of tumor cell responses to drugs, is particularly important for cancers lacking actionable genomic...

Microvascular inflammation in the kidney transplant, beyond acute antibody-mediated rejection.

PURPOSE OF REVIEW: Microvascular inflammation (MVI) is a central feature of allograft rejection, traditionally associated with antibody-mediated rejec...

From inhibition to regulation: serpins in health and disease.

This issue of the Biomedical Journal highlights regulatory mechanisms that shape aging, disease progression, and biological complexity across molecula...

Evolution of root nodule symbiosis via paleopolyploidy and modular pathway rewiring.

The evolution of root nodule symbiosis (RNS), a key innovation for plant nitrogen acquisition, has long been studied but lacks a mechanistic, gene-lev...

Identification of Pyrrolo[2,3-d]pyrimidine-Based Dual MERTK and FLT3 Inhibitor: Hit-to-Lead, Machine Learning, Modeling, Synthesis, and Biological Evaluation.

Overexpression of MERTK and FLT3 plays a crucial role in activating signal transduction pathways in various human hematological malignancies. These si...

Forecasting Waitlist Trajectories for Patients With Metabolic Dysfunction-Associated Steatohepatitis Cirrhosis: A Neural Network Competing Risk Analysis.

BACKGROUND: Metabolic dysfunction-associated steatohepatitis (MASH) cirrhosis is a leading indication for liver transplantation (LT). Patients with MA...

HRD-Informed Digital Histology Model for Predicting Platinum Chemo-Response and Prognosis in High-Grade Serous Ovarian Cancer.

Homologous recombination deficiency (HRD) is a critical biomarker in high-grade serous ovarian cancer for the clinical benefit from platinum-based che...

Clinically aligned whole-body MRI segmentation of skeletal metastases via Supervised Anatomical Pretraining.

In oncology practice, response assessment of metastatic disease requires reliable and reproducible quantification of measurable metastatic burden. Man...

Comparative study on predicting postoperative distant metastasis of lung cancer based on machine learning models.

Lung cancer remains the leading cause of cancer-related incidence and mortality worldwide. Its tendency for postoperative distant metastasis significa...

Multi-Model Fusion for 28-Day Mortality Prediction in ICU Patients: A Comprehensive Retrospective Cohort Study with Subgroup Validation and Clinical Risk Stratification.

BACKGROUND: Accurate prediction of 28-day mortality in intensive care unit (ICU) patients represents a critical challenge in modern critical care medi...

Feasibility study of fast T2-weighted imaging with deep-learning reconstruction in volunteers and emergency patients with acute abdomen.

PURPOSE: To evaluate the image quality and clinical utility of DLR-enhanced single-shot fast spin-echo (SSFSE) T2-weighted imaging (T2WI) for diagnosi...

Prognostic value of the triglyceride-glucose index combined with atherogenic index of plasma for all-cause mortality in critically ill patients with chronic heart failure: a machine learning-driven retrospective cohort study.

BACKGROUND: The triglyceride-glucose index (TyG) and atherogenic index of plasma (AIP) are emerging metabolic biomarkers associated with cardiovascula...