Oncology/Hematology

Deep learning and radiomics fusion for predicting the invasiveness of lung adenocarcinoma within ground glass nodules.

Microinvasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC) require distinct treatment stra...

Next-generation AI framework for comprehensive oral leukoplakia evaluation and management.

Oral potentially malignant disorder poses a significant risk of malignant transformation, particular...

Prediction of cervical cancer lymph node metastasis based on multisequence magnetic resonance imaging radiomics and deep learning features: a dual-center study.

Cervical cancer is a leading cause of death from malignant tumors in women, and accurate evaluation ...

From lab to life: technological innovations in transforming cancer metastasis detection and therapy.

Prediction of Early Recurrence After Bronchial Arterial Chemoembolization in Non-small Cell Lung Cancer Patients Using Dual-energy CT: An Interpretable Model Based on SHAP Methodology.

RATIONALE AND OBJECTIVES: Bronchial artery chemoembolization (BACE) is a new treatment method for lu...

Prediction of Benign and Malignant Small Renal Masses Using CT-Derived Extracellular Volume Fraction: An Interpretable Machine Learning Model.

RATIONALE AND OBJECTIVES: We developed a machine learning model comprising morphological characteris...

Pharmacovigilance in Cell and Gene Therapy: Evolving Challenges in Risk Management and Long-Term Follow-Up.

Cell and gene therapies, including CAR T-cells, CRISPR-based genome editing, and next-generation vir...

Deep learning model for early acute lymphoblastic leukemia detection using microscopic images.

Cancer of bone marrow is classified as Acute Lymphoblastic Leukemia (ALL), an abnormal growth of lym...

Non-coding genetic elements of lung cancer identified using whole genome sequencing in 13,722 Chinese.

A substantial portion of lung cancer-associated genetic elements in East Asian populations remains u...

Ligand supplementation restores the cancer therapy efficacy of the antirheumatic drug auranofin from serum inactivation.

Auranofin, an FDA-approved antirheumatic gold drug, has gained ongoing interest in clinical studies ...

Machine learning-driven multi-omics analysis identifies a prognostic gene signature associated with programmed cell death and metabolism in hepatocellular carcinoma.

Exploring the feasibility of AI-based analysis of histopathological variability in salivary gland tumours.

This study uses artificial intelligence (AI) for differentiation between salivary gland tumours (SGT...

Oral cancer detection via Vanilla CNN optimized by improved artificial protozoa optimizer.

In this study, we propose a new method for oral cancer detection using a modified Vanilla Convolutio...

Reframing robotics in Mohs surgery for rare cutaneous sarcomas: conceptual promise and clinical realities in precision oncology.

Dermatofibrosarcoma protuberans (DFSP) is a rare, locally aggressive cutaneous sarcoma in which achi...

Research trends in cervical cancer brachytherapy: a bibliometric analysis.

BACKGROUND: Cervical cancer (CC) was a significant gynecological malignancy. Brachytherapy (BT) has ...

Multi-institutional study for comparison of detectability of hypovascular liver metastases between 70- and 40-keV images: DELMIO study.

PURPOSE: To compare the lesion detectability of hypovascular liver metastases between 70-keV and 40-...

Value of artificial intelligence in neuro-oncology.

CNS cancers are complex, difficult-to-treat malignancies that remain insufficiently understood and m...

Artificial intelligence in radiology, nuclear medicine and radiotherapy: Perceptions, experiences and expectations from the medical radiation technologists in Central and South America.

INTRODUCTION: Artificial intelligence (AI) has been growing in the field of medical imaging and clin...

Development and validation of interpretable machine learning models for predicting AKI risk in patients treated with PD-1/PD-L1: a retrospective study.

BACKGROUND: Anti-programmed cell death protein 1 (PD-1)/programmed cell death ligand 1 (PD-L1) immun...

Deep learning-based image enhancement for improved black blood imaging in brain metastasis.

OBJECTIVES: To evaluate the utility of a deep learning (DL)-based image enhancement for improving th...

Breast cancer is detectable from peripheral blood using machine learning over T cell receptor repertoires.

The immune system's defense abilities rely on the diversity of T and B lymphocytes. T Cell Receptors...