Leukemia

Association between stress hyperglycemia ratio and all-cause mortality in neurocritical patients.

Fluctuations in blood glucose during acute neurocritical illness are associated with poor outcomes, but the role of stress hyperglycemia ratio (SHR) in predicting outcomes across diverse neurocritical conditions remains unclear. This study evaluated SHR as a prognostic indicator for short and long-term mortality and its utility in machine learning-enhanced predictive models. Using data from the Me...

Predicting VRE Infection After Liver Transplantation With a Time-Updated Colonization Score.

BACKGROUND: Vancomycin-resistant Enterococcus (VRE) infection is a life-threatening complication after liver transplantation (LT). This study aimed to identify risk factors and develop a predictive score for post-transplant VRE infection in LT recipients. METHODS: We conducted a single-center, retrospective cohort study including all adult patients who underwent LT between 2010 and 2022. Patients ...

Integrated analysis of therapeutic strategies and prognostic factors in advanced lung adenocarcinoma: Retrospective study with emphasis on gene assays, multimodality treatment approaches and predictive machine learning models.

Patients with advanced lung adenocarcinoma have a range of treatment options, including targeted therapy and gene assay-guided chemotherapy. The aim o...

Artificial Intelligence for T classification of TNM breast cancer in MRI imaging: Enabling Precision in Treatment Decisions.

The integration of artificial intelligence (AI) into breast cancer management presents transformative potential for both diagnosis and treatment plann...

CAR T-cells in hematologic malignancies: Advances, challenges, and future directions.

Chimeric antigen receptor (CAR) T-cell therapy has transformed the management of hematologic malignancies, achieving high remission rates in relapsed ...

Bytes to Blood-Artificial Intelligence in the Management of Leukemia: A 2025 Update.

As artificial intelligence (AI) has been proposed to aid in the clinical management of leukemia, we sought to summarize the most relevant, current lit...

Integrating ensemble machine-learning and fibril docking to discover potent, novel triazole-naphthalene tau-aggregation inhibitors.

Tau-protein aggregation is a central pathological feature of Alzheimer's disease, so blocking fibril growth is an attractive therapeutic goal. We cura...

Radiomics features as imaging biomarkers in alveolar and craniofacial bone healing: a scoping review.

Radiomics has emerged as a promising approach for quantifying bone regeneration by extracting high-dimensional features from routine imaging data. Thi...

Early electrocardiographic repolarization changes are associated with subclinical cancer therapy-related cardiac dysfunction in lymphoma patients: A machine learning-assisted longitudinal study.

UNLABELLED: Anthracycline-induced cardiotoxicity remains a significant clinical challenge. We evaluated longitudinal electrocardiographic (ECG) repola...

Neoadjuvant Systemic Therapy in Kidney and Bladder Cancer: Current Evidence and Emerging Paradigms.

Neoadjuvant systemic therapy has emerged as a strategy to improve outcomes in high-risk localized genitourinary malignancies. In bladder cancer, neoad...

Computer-aided drug design in acute myeloid leukemia: a comprehensive review of advances, challenges, and future prospect.

Deep learning ensemble models for CT-based differentiation of malignant and benign sacral bone tumors: development and evaluation.

OBJECTIVE: Radiologists often face challenges in differentiating benign from malignant sacral bone lesions due to their similar imaging characteristic...

Influence of body composition on the efficacy of nivolumab plus ipilimumab for metastatic clear cell renal cell carcinoma.

BACKGROUND: Immune checkpoint inhibitor therapy (ICI) with nivolumab+ipilimumab is a first-line (1L) standard for metastatic clear cell renal cell car...

AI fragmentation-based optimization of Sorafenib derivatives targeting VEGFR2 for angiogenesis-related pathologies: a structure-based in-silico study.

Vascular endothelial growth factor receptor 2 (VEGFR2) is a central regulator of angiogenesis and endothelial signaling and represents a validated the...

Minimally invasive surgery for advanced-stage ovarian cancer: a review of evidence and emerging paradigms.

Minimally invasive surgery has emerged as a promising approach to the management of advanced-stage epithelial ovarian cancer, particularly in the sett...

Cluster-Based MR Radiomics Model for Predicting Induction Chemotherapy Response in Nasopharyngeal Carcinoma.

RATIONALE AND OBJECTIVES: To develop a cluster-specific magnetic resonance (MR) radiomics model for predicting induction chemotherapy (ICT) response i...

Prediction of Neoadjuvant Chemotherapy Efficacy for Locally Advanced Nasopharyngeal Carcinoma Using MRI-Based Deep Learning Features Combined with Vision Transformer.

RATIONALE AND OBJECTIVES: Predicting neoadjuvant chemotherapy (NACT) efficacy is vital for advanced nasopharyngeal carcinoma (LA-NPC) management. Exis...

Characterization of the Sequence of Cytopenia after Total-body Irradiation using Unsupervised Machine Learning.

Hematopoietic acute radiation syndrome (H-ARS) elicits multidimensional effects, as total-body irradiation (TBI) induced myelosuppression results in d...

Chest Computed Tomography-Based Radiomics and Machine Learning for Classifying Mediastinal Lymphadenopathy Caused By Hematologic Malignancies and Metastatic Abdominopelvic Solid Cancers.

PURPOSE: To evaluate the role of chest CT radiomics in classifying mediastinal lymphadenopathy caused by hematologic malignancies and abdominopelvic s...

Optimizing Fixed-Duration Ven-I Regimen in CLL: Expert Insight and AI Comparison.