Oncology/Hematology

Predicting the risk of venous thromboembolism events in older adults with rheumatoid arthritis after initiating targeted disease-modifying antirheumatic drugs: a comparison of the random survival forest and regularized cox regression models.

OBJECTIVES: To develop a random survival forest (RSF) machine learning (ML) model for predicting venous thromboembolism (VTE) risk in rheumatoid arthritis (RA) patients initiating biological (b) or targeted synthetic (ts) disease-modifying antirheumatic drugs (DMARDs) and compare its model performance with a regularized Cox regression (RegCox) model. METHODS: This retrospective cohort study using ...

Testing Near-Field Radio-Frequency Sensors to Predict Respiratory Distress in Patients Living With Dementia: A Pilot Feasibility and Acceptability Study.

BackgroundPeople living with dementia (PLWD) with advanced illness are prone to respiratory distress yet often cannot self-report dyspnea, delaying recognition and treatment. Near-field radio-frequency (NFRF) sensors offer touchless, covert cardiopulmonary monitoring that may be better tolerated than tethered devices.ObjectivesTo assess the feasibility and acceptability of NFRF bed sensor for home...

Diagnostic Proficiency of Large Language Models in the Interpretation of Cervical Cytopathology.

To evaluate the diagnostic proficiency of well-established multimodal Large Language Models (LLMs)-specifically Gemini, Claude, and Copilot-in interpr...

National Institute of Allergy and Infectious Diseases (NIAID) - Bundeswehr Institute of Radiobiology (BIR) Joint Programmatic Workshop on a Global Approach to Medical Countermeasure Development in Radiological Public Health Preparedness.

This invited commentary grew out of a presentation made at the 2025 ConRad Meeting in Munich, Germany, and summarizes talks made by researchers suppor...

Positron emission tomography imaging of inflammation and infection in children: an update.

Positron emission tomography (PET) has been used in pediatric oncology since the modality gained traction 20 years ago but has been used more sparingl...

High risk score of breast cancer by artificial intelligence (AI) on screening mammograms: a review of negative and cancer cases.

OBJECTIVES: To investigate mammographic features associated with high artificial intelligence (AI) risk scores as provided by two AI models applied to...

Multidimensional immune ecological subtyping identifies RUNX1 as a prognostic factor in uveal melanoma.

Uveal melanoma (UVM) is an aggressive intraocular malignancy with a high risk of metastasis but few effective therapies. However, current molecular cl...

Improving predicted risk of recurrence using molecular profiling in papillary thyroid cancer.

Molecular testing can refine the prediction of cancer recurrence. We sought to compare patterns of gene expression in patients with and without recurr...

Non-invasive profiling of the tumour microenvironment with spatial ecotypes.

Multicellular programs in the tumour microenvironment (TME) drive cancer pathogenesis and response to therapy but remain challenging to identify and p...

A network medicine framework for multi-modal data integration in therapeutic target discovery.

The high cost and attrition rate of drug development underscore the need for more effective strategies for therapeutic target discovery. Here, we pres...

Design and in silico evaluation of an mRNA vaccine against HTLV-1 using AI-driven reverse vaccinology approaches.

Human T-lymphotropic virus type 1 (HTLV-1) is the first discovered human oncogenic retrovirus that can cause adult T-cell leukemia/lymphoma, HTLV-1-as...

Robust disease prognosis via diagnostic knowledge preservation: A sequential learning approach.

Accurate disease prognosis is essential for patient care but is often hindered by the scarcity of longitudinal data. This study explores deep learning...

Personalized risk prediction of financial toxicity in patients with cancer: an interpretable machine learning study.

BACKGROUND: Financial toxicity (FT), the economic stress from medical care, is common among people with cancer and is associated with worse health out...

Examination of Pathologist-Artificial Intelligence Interactions and Their Impact on Pathologist Accuracy Using Artificial Intelligence-Assisted Scoring of Immunohistochemistry for Human Epidermal Growth Factor Receptor 2.

CONTEXT.—: Advances in computer vision have fueled the development of artificial intelligence (AI)-based algorithms for pathology. AI-assisted approac...

Applying Artificial Intelligence Technologies to Detect Pancreatic Ductal Adenocarcinoma Using Routine Laboratory Tests: A Pilot Study with the Aid of Machine Learning Suitable for a Small Data Analysis.

Objective This study aimed to investigate whether artificial intelligence could identify pancreatic ductal adenocarcinoma (PDAC) in patients aged <70 ...

Focused Ultrasound in Brain Tumors: Mechanisms, Imaging Guidance, and Emerging Clinical Applications.

Focused ultrasound (FUS) is an emerging therapeutic and diagnostic technology in neuro-oncology, offering new strategies for molecular diagnosis, drug...

A Biomimetic Nanozyme Engineered via Coordination and Confinement for Photothermal-Reinforced Catalytic Detection of Extracellular Vesicles and Diagnosis of Cancer.

Extracellular vesicles (EVs) have emerged as promising biomarkers for liquid biopsy. However, their clinical detection is hampered by heterogeneity an...

Precision animal models of tumors: Advances, challenges and clinical translation.

Preclinical immunotherapy research relies heavily on animal tumor models, which can be broadly classified into four categories: genetically engineered...

Integrating QSAR-Machine Learning, Biochemical Assays, and Molecular Dynamics for the Discovery of JAK2 Inhibitors in Cervical Cancer.

Cervical cancer remains a major global health challenge, where dysregulated JAK2 signaling constitutes a key molecular driver. Nevertheless, selective...

CellFuse enables Multi-modal Integration of Single-cell and Spatial Proteomics Data for Systems-level Analysis in Cancer.

Analysis of tumors using single-cell and spatial modalities is critical to advance our understanding of cancer. The growth of technologies that enable...