Oncology/Hematology

Machine Learning to Predict Remission Between Six and 24 Months in Rheumatoid Arthritis: Insights from the JAK-pot Collaboration.

OBJECTIVE: To develop, externally validate, and simplify a machine-learning (ML) model to predict re...

Deep learning reconstruction for 40-keV virtual monoenergetic CT of colon cancer: evaluation of image quality and edge sharpness.

BACKGROUND: Virtual monoenergetic imaging (VMI) at 40 keV improves iodine attenuation in colon cance...

Artificial Intelligence-Enabled Prediction of Reversible Versus Irreversible Chemotherapy-Induced Myocardial Injury: Toward Precision Cardio-Oncology.

Cancer therapy-related cardiac dysfunction remains a major cause of morbidity among cancer survivors...

Deep Learning-based Segmentation for Assessment of Kidney Tumour Ablation Therapy in CT Images.

Kidney tumor ablation is a minimally invasive treatment for Renal Cell Carcinoma (RCC). Manual segme...

HCCaging: a liver physiological aging-related biomarker for hepatocellular carcinoma diagnosis based on transcriptome data.

Aging is a fundamental biological process that influences cancer development in a context-dependent ...

Lipid Metabolism and Oxidative Stress in Uterine Corpus Endometrial Carcinoma: Prognostic and Immune Landscape Analysis.

OBJECTIVE: Uterine corpus endometrial carcinoma (UCEC) is a common gynecologic malignancy characteri...

A fully automated CT-based pelvimetry pipeline for quantifying mid-pelvic surgical workspace in rectal cancer.

PURPOSE: Pelvimetry may aid preoperative planning in rectal cancer surgery, yet manual measurements ...

Integration of multi-omics and machine learning to identify core genes in PANoptosisof lung adenocarcinoma and their mechanisms in the tumor microenvironment and therapeutic potential.

Lung adenocarcinoma (LUAD) is one of the leading causes of cancer-related deaths worldwide, and its ...

Integrative multi-omics identifies a diagnostic T cell signature for cutaneous squamous cell carcinoma.

Cutaneous squamous cell carcinoma (cSCC) involves complex immune interactions. This study aimed to i...

Physics-constrained multimodal vision transformer for ultra-short-term solar radiation forecasting error correction.

Accurate ultra-short-term solar radiation forecasting is critical for renewable energy integration a...

Uncovering Global Trends in Surgical Oncology Trials: Applying Natural Language Processing to ClinicalTrials.gov.

BACKGROUND: Identifying surgical oncology trials within the National Clinical Trial (NCT) database i...

LILRB3 inhibition reverses immunosuppression in glioma: a nanoparticle-based therapeutic strategy.

Glioma is a highly aggressive brain tumor characterized by a profoundly immunosuppressive tumor micr...

Integrating experimental findings and machine learning models to predict the anticancer potential of newly synthesized oversulfated fucoidan.

Developing effective cancer treatments requires identifying novel therapeutic agents with high biolo...

Mapping intratumoral heterogeneity through PET-derived washout and deep learning after proton therapy.

The distribution of produced isotopes during proton therapy can be imaged with Positron Emission Tom...

FDG PET in pulmonary sarcoidosis: An update and future aspects.

Pulmonary sarcoidosis is a heterogeneous granulomatous disease with an unpredictable clinical course...

Mapping whole-organism genetic comorbidities across model Species using unified ontologies.

Understanding how genetic variation contributes to organism-wide phenotypes is critical for identify...

Dual-layer spectral CT for predicting spread through air spaces in lung adenocarcinoma: a dual-center study.

OBJECTIVES: To investigate the value of machine learning classifiers incorporating dual-layer spectr...

Integration of machine learning-based screening approaches and single-cell sequencing technique to identify cancer stemness genes associated with radiotherapy resistance in lung adenocarcinoma.

Circulating Immune Profiles in ACTH-Dependent Cushing's Syndrome.

OBJECTIVE: ACTH-dependent Cushing's syndrome (CS) causes profound immune dysfunction and severe infe...

A deep learning-based multimodal model with automated body composition analysis predicts prognosis in advanced clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is an aggressive malignancy with a high risk of postoperativ...

scAgeClock: a single-cell transcriptome-based human aging clock model using gated multi-head attention neural networks.

Aging clock models have emerged as a crucial tool for measuring biological age, with significant imp...