Leukemia

Multi-variant GWAS and genomic prediction dissect the genetic architecture underlying tomato fruit weight.

Tomato fruit weight is primarily controlled by stable genetic effects and domestication-/improvement-associated loci, including prominent chromosome 5 signals, and integrating SNP, INDEL, and SV diversity improves candidate-locus discovery, biological interpretation, and genomic prediction across environments. Tomato fruit weight (fw) is a major breeding target shaped by domestication, crop improv...

A novel framework for the discovery of MAPK-activated protein kinase 2 (MAPKAPK2) inhibitors using a multi-feature deep learning ensemble.

MAPKAPK2 is a promising therapeutic target in numerous diseases. However, many MAPKAPK2 inhibitors are plagued by low solubility and permeability, and none have advanced through clinical trials. New computational methods utilizing deep learning can speed up inhibitor identification. This study aims to develop and validate a novel framework for MAPKAPK2 inhibitor discovery utilizing an ensemble of ...

Dual-Approach AI for Pediatric Supracondylar Fractures: Multiclass Radiograph Classification with Explainable AI and Diagnostic Meta-analysis of AI-Based Computational Approaches.

RATIONALE AND OBJECTIVES: Pediatric supracondylar fractures (SCFs) are the most common elbow injury in children, yet radiographic diagnosis remains ch...

Automated detection of active and structural MRI lesions in the sacroiliac joints in axial spondyloarthritis: training and validation across 3 phase III clinical trial datasets.

OBJECTIVES: This study aims to assess the performance of a fully automated deep learning (DL) system for detecting active and structural magnetic reso...

Combating New Delhi metallo-beta-lactamase-1 (NDM-1): an integrated review of inhibitor development and next-generation therapeutic platforms.

New Delhi metallo-β-lactamase-1 (NDM-1), which has emerged globally, exhibits resistance to almost all β-lactam antibiotics, including carbapenems, po...

Artificial Intelligence for Diagnosis, Risk Stratification, and Prognosis of Neuroblastoma - A Systematic Review and Meta-Analysis.

PURPOSE: To synthesizes evidence on artificial intelligence (AI) performance in neuroblastoma (NB) diagnosis, risk stratification, prognosis, and geno...

Comparison of Pleomorphic Dermal Sarcoma to Advanced Cutaneous Squamous Cell Carcinoma and Soft-Tissue Sarcoma.

IMPORTANCE: Pleomorphic dermal sarcomas (PDSs) are classified as sarcomas; however, they share features with cutaneous carcinomas, such as presentatio...

A formal Bayesian decisional framework for automated cell subset assignment in multiparametric flow cytometry: The LBC-flow approach.

Multiparametric flow cytometry (MFC) data analyses still largely rely on expert-dependent subjective manual gating strategies. While unsupervised clus...

Development and validation of a machine learning model based on routine laboratory tests for predicting FLT3-ITD mutations in acute myeloid leukaemia.

Feline McDonough sarcoma (FMS)-like tyrosine kinase 3 internal tandem duplication (FLT3-ITD) mutations are clinically important in acute myeloid leuka...

Automated segmentation and length measurement of metacarpal and phalangeal bones for hand radiograph evaluation.

Evaluating hand and wrist radiographs is essential in pediatric endocrinology and clinical genetics, particularly for the assessment of suspected skel...

Discovery of novel acridine based inhibitors of Bruton's tyrosine kinase (BTK) via pharmacophore modeling and machine learning-driven virtual screening followed by molecular dynamic studies.

Bruton's Tyrosine Kinase (BTK) has been recently recognized as an important drug design target for treating B-cell malignancies. Unfortunately, drug r...

Integrating Target Prediction and Transcriptomic Analysis Identifies the AKR1C2-KRT8 Axis in Rotenone-Induced Dopaminergic Neuron Injury.

Parkinson's disease (PD) is a complex neurodegenerative disorder in which environmental toxins play a critical etiological role. Rotenone, a classical...

Artificial intelligence-assisted identification of skin lesions associated with chronic venous insufficiency.

OBJECTIVE: This study aimed to develop and validate a deep learning framework to classify chronic venous insufficiency - related skin lesions and diff...

Development and external validation of a contrastive learning foundation model for ECG-based prediction of cardiovascular diseases and outcomes.

BACKGROUND: Automated electrocardiogram (ECG) assessment tools to assist clinicians in diagnosis have improved substantially over the past decade; how...

Navigating Human Astrocyte Differentiation: Direct and Rapid One-Step Differentiation of Induced Pluripotent Stem Cells to Functional Astrocytes Supporting Neuronal Network Development.

Astrocytes play a pivotal role in neuronal network development. Despite the well-known role of astrocytes in the pathophysiology of neurologic disorde...

Impacted Bones: Can Extant Primates Help Identify Tool Use in Early Hominins?

Despite recent advances pushing back the earliest record of tool use, how and when it first emerged in hominins, and the extent to which it featured a...

Diagnostic performance of artificial intelligence models trained on scattered single-cell images is not preserved for hyperchromatic crowded cell groups in cervical cytology.

BACKGROUND: Deep learning has shown promising performance in cervical cytology; however, many studies have relied on presegmented single-cell images r...

Manual, digital, and AI tumour-infiltrating lymphocyte scoring: a secondary analysis of the APHINITY randomised trial.

BACKGROUND: Stromal tumour-infiltrating lymphocytes (sTILs) are prognostic in early-stage HER2-positive breast cancer, but their role in the context o...

Automating cost-effectiveness models with agentic artificial intelligence: Case study and implications for value assessment.

BACKGROUND: Health economic modeling is conceptually sophisticated but operationally repetitive and resource intensive. Recent advances in large langu...

Integration of Artificial Intelligence Models and Logistic Regression to Increase the Diagnostic Accuracy of Acute Appendicitis.

BACKGROUND/AIM: In patients with acute abdominal pain (AAP), the accuracy of artificial intelligence (AI) models in the diagnosis of acute appendiciti...