Leukemia

Correlation between artificial intelligence-based IDAScore and embryo morphokinetic parameters: a retrospective cohort study.

PURPOSE: The rapid advancement of artificial intelligence (AI) has brought new opportunities for embryo evaluation. The integration of AI with time-lapse (TL) imaging technology has significantly enhanced the pregnancy rates in assisted reproductive technologies (ART). However, the fully automated AI-based embryo screening model, IDAScore lacks transparency and specific justifications in assessing...

Deep-learning CT reconstruction improves image quality but not diagnostic accuracy for sacral fragility fractures: MRI remains essential.

PURPOSE: To determine whether modern deep-learning CT reconstruction improves trauma-relevant diagnostic performance for sacral fragility fractures (SFF) and whether optimized CT can reduce the need for MRI in routine clinical practice. METHODS: In this retrospective paired-reader study, 171 pelvic CT examinations with corresponding MRI (reference standard) were analyzed (fracture prevalence 63.2%...

Development and internal validation of an interpretable machine learning model using routine laboratory data for systemic sclerosis-associated pulmonary arterial hypertension.

This study aimed to develop and validate an interpretable machine learning (ML) model using routine laboratory data to support clinical decision-makin...

Machine Learning-Augmented Traditional Analysis of Lactate vs Lactate-to-Albumin Ratio for Predicting Mortality Risk in Patients With Sepsis: Large-Scale Retrospective Study.

BACKGROUND: Effective risk stratification in sepsis remains a critical clinical challenge. Serum lactate is a cornerstone biomarker of metabolic dysfu...

A Multimodal Deep Learning Model for Preoperative Prediction of Postoperative Complications in Gastric Cancer.

BACKGROUND: Clavien-Dindo (CD) grade ≥II complications occur in roughly one in five patients after curative gastrectomy for gastric cancer and indepen...

Deep Learning Predicts Imminent Tumor Progression in Advanced Pancreatic Adenocarcinoma Using Serial CT Scans During Chemotherapy.

Advanced pancreatic ductal adenocarcinoma (PDAC) often progresses rapidly during chemotherapy despite initial assessments of stable disease or partial...

Functionally Guided Graph Learning for Robust Cross-Patient Cell-Type Annotation in Single-Cell RNA Sequencing.

Cross-patient cell-type annotation in single-cell RNA sequencing (scRNA-seq) remains challenging due to pronounced interpatient heterogeneity and dist...

Improving hard-to-place kidney allocation: A machine learning approach to center ranking.

Kidney transplantation is the preferred treatment for end-stage renal disease, yet donor scarcity and inefficiencies in allocation systems create majo...

CMTM3 links inflammation-related transcriptional dysregulation to immune and therapeutic stratification in gastric cancer.

Gastric cancer (GC) shows strong biological heterogeneity and frequent disruption of inflammatory and metabolic programs, which affect tumor progressi...

Unraveling the Mechanism of Drug Binding to SARS-CoV-2 RNA Pseudoknot With Thermodynamics-Driven Machine Learning.

The pseudoknot secondary structure in SARS-CoV-2 RNA is essential for regulating protein synthesis through - $$ - $$ 1 programmed ribosomal frameshi...

Machine learning-guided discovery of withangulatin A as a novel inducer of megakaryocytic differentiation through direct targeting of TYK2 in leukemia.

BACKGROUND: Leukemia is an aggressive hematological malignancy. Effective differentiation-inducing agents for non-acute promyelocytic leukemia (non-AP...

Integrating MRI radiomics and deep learning for predicting pathologic complete response to neoadjuvant chemotherapy in breast cancer: a multicenter study.

OBJECTIVE: Develop a multimodal fusion model combining MRI radiomics and deep learning (DL) to predict pathologic complete response (pCR) in breast ca...

Gut microbiome in pediatric acute pancreatitis and Crohn's disease versus irritable bowel syndrome and healthy controls.

OBJECTIVES: Pediatric acute pancreatitis (AP), Crohn's disease (CD), and irritable bowel syndrome (IBS) are associated with gut dysbiosis, but differe...

Atomic Uncertainty Pinpoints Critical Failure Structures for Trustworthy Molecular Property Prediction.

Accurate prediction of molecular properties is essential for accelerating drug discovery, yet current deep learning methods generally lack reliable un...

Explainable Ensemble Learning With Stain Normalization and Deep Feature Extraction for Acute Lymphoblastic Leukaemia Classification.

Acute lymphoblastic leukaemia (ALL), a common form of cancer, remains a life-threatening condition that affects individuals worldwide, including both ...

Comparing machine learning methods predicting transcriptome from epigenome with applications to association studies.

BACKGROUND: Understanding how epigenome variation contributes to gene expression in disease and development is a fundamental challenge. Regulatory reg...

Pharmacogenomics in oncology: mutation-targeted therapy and biomarker integration in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is the most common cancer-related cause of death among all countries globally, mostly because of late diagnosis, he...

Disease-modifying antirheumatic drugs (DMARDs) for rheumatoid arthritis after failure of biologic or targeted synthetic therapy: a systematic review and network meta-analysis.

RATIONALE: After inadequate response to first-line biologic or targeted synthetic (b/ts) disease-modifying antirheumatic drug (DMARD) therapy in adult...

Self-explaining artificial intelligence for the classification of B cell non-Hodgkin lymphoma: A diagnostic decision support study.

BACKGROUND: Multiparameter flow cytometry is a cornerstone of B cell non-Hodgkin lymphoma (B-NHL) diagnostics, but interpretation requires substantial...

Machine learning-based prediction of overall survival in non-metastatic renal cell carcinoma after radical nephrectomy.

Prognostic heterogeneity remains a challenge for non-metastatic renal cell carcinoma (RCC) patients following radical nephrectomy (RN). This study aim...