Leukemia

The association of systemic inflammatory indices with all-cause mortality risks in patients with COPD: A cohort study based on machine learning.

This study aimed to comprehensively assess the prognostic value of routinely obtained blood-based systemic inflammatory indices in predicting all-cause mortality among individuals with chronic obstructive pulmonary disease (COPD). This retrospective cohort study analyzed data from the National Health and Nutrition Examination Survey (NHANES) cycles 2007-2010. A total of 1109 eligible adults with C...

Clinical Significance of Biomarkers in Oropharyngeal Squamous Cell Carcinoma: Recurrence Prediction and Treatment Response.

BACKGROUND: Oropharyngeal squamous cell carcinoma (OPSCC) accounts for a substantial proportion of head and neck cancers, with a rising incidence largely driven by human papillomavirus (HPV) infection. Despite advances in multimodal treatment, disease recurrence remains common and limits long-term survival, highlighting the need for reliable biomarkers to guide prognosis and treatment. METHODS: Th...

Transcriptome-based Deep Learning Model for Predicting Gemcitabine and Cisplatin Chemotherapy Response in Urothelial Carcinoma: Development and External Validation.

BACKGROUND/AIM: Chemotherapy with gemcitabine and cisplatin remains the cornerstone of treatment for advanced urothelial carcinoma (UC), yet response ...

In silico identification of NPACT-derived PAK1 inhibitors using machine learning, molecular docking, and dynamic simulation approaches.

P21-activated kinase 1 (PAK1) is a key serine/threonine kinase involved in cytoskeletal remodeling, cell proliferation, and survival, and its aberrant...

An integrative machine learning and structure-driven drug repositioning strategy for human IRAK4-targeted cancer therapy.

The upregulation of interleukin-1 receptor-associated kinase 4 (IRAK4) drives pro-tumorigenic signaling across various malignancies. Currently availab...

Integrating single-cell RNA and bulk RNA sequencing data to identify prognostic genes associated with pyrimidine metabolism in triple-negative breast cancer by machine learning algorithm combinations.

BACKGROUND: Pyrimidine metabolism plays a crucial role in DNA synthesis and cell proliferation and is associated with the development of various cance...

Imaging of ewing sarcoma: an updated analysis including presenting features, prognostic imaging biomarkers, and treatment response assessment.

Ewing sarcoma is a highly aggressive small round cell sarcoma primarily affecting children and adolescents. Imaging plays a central role from diagnosi...

Predicting survival of Hodgkin lymphoma using machine learning-an analysis based on the SEER database.

OBJECTIVES: This study aimed to develop an effective model for predicting Hodgkin lymphoma (HL) prognosis as to assist clinicians in making optimal cl...

The Negative Impact of a Non-Therapeutic Laparotomy in Patients With Inoperable Colorectal Peritoneal Metastases.

BACKGROUND: The peritoneum is the third most prevalent location for metastases of colorectal cancer. In patients with resectable disease, cytoreductiv...

Quantitative CT Measurements of Interstitial Lung Disease: Same-Day Variability Between Two Vendors-A Prospective Study.

BACKGROUND. Clinical application of quantitative CT (QCT) measurements of interstitial lung disease (ILD) for longitudinal monitoring of disease progr...

DeepKinomeWeb: a quantitative, panel-level platform for kinase inhibitor screening and selectivity profiling.

Protein kinases are central targets in drug discovery, yet early-stage development of potent and selective inhibitors remains challenging due to high ...

Random Survival Forest Versus Elastic-Net Regularized Cox Regression for Survival Prediction in Acute Myeloid Leukemia at Distinct Treatment Time Points: Model Performance Comparison Study.

BACKGROUND: Risk group stratification based on the prediction of survival of patients with acute myeloid leukemia (AML) is complex. Despite common ris...

Evolution and forecasting of antiretroviral therapy utilisation in British Columbia: a population-level analysis of provincial drug treatment programme data, 2014-2024.

OBJECTIVE: To characterise temporal trends in antiretroviral therapy (ART) utilisation and forecast short-term changes in regimen distribution within ...

Sex-Specific Prognostic Value of Left Atrioventricular Coupling Index in Acute Coronary Syndrome: Insights From Artificial Intelligence-Enhanced 3-Dimensional Echocardiography.

BACKGROUND: Left atrioventricular coupling index (LACI) has emerged as a prognostic biomarker, but its sex-specific relevance in acute coronary syndro...

Graph augmented transformers improve chemotherapy toxicity symptom extraction from clinical notes.

Chemotherapy is essential for cancer treatment but may cause adverse events requiring emergency department visits and hospitalizations, placing substa...

Multi-Omics and Machine Learning Analyses Reveal PIK3CG, PRKCD, and TRIM22 as Potential Markers of Poor Prognosis and Immune Activation in Glioblastoma.

BACKGROUND: Glioblastoma (GBM) is one of the most aggressive brain tumors with a poor prognosis despite current treatment modalities. This study aimed...

Deep Learning Reconstruction Versus Hybrid Iterative Reconstruction for Acute Cerebral Infarction Detection on 135 kVp Non-Contrast Brain CT.

PURPOSE: Deep learning reconstruction (DLR) is useful to reduce image noise and improve contrast resolution compared with hybrid iterative reconstruct...

Comprehensive validation of machine learning models predicting chemotherapy related electrolyte disorders in a multicenter study.

BACKGROUND: Electrolyte abnormalities following chemotherapy are common and clinically significant complications in cancer patients and are often asso...

Evaluation of artificial intelligence-based software programs applied to the radiographic and photographic identification of dental implant systems.

PURPOSE: The purpose of this evaluation study was to assess the performance of ChatGPT-5, Google Gemini (v2.5), and Microsoft Copilot in identifying f...

Monotherapy cancer drug-blind response prediction is limited to intraclass generalization.

Monotherapy cancer drug response prediction (DRP) models predict the response of a cell line to a given drug. Analyzing these models' performance incl...