Oncology/Hematology

The SPECT/CT radiomics-based classification of skeletal metastases and benign bone lesions.

Hybrid Single Photon Emission Computed Tomography/Computed Tomography (SPECT/CT) improves lesion localization and diagnostic accuracy in detecting skeletal metastases. However, interpretation based on standardized uptake value (SUV) remains suboptimal due to overlapping uptake between benign and malignant lesions. Radiomics quantifies intralesional heterogeneity and may overcome SUV limitations. T...

Artificial intelligence in cancer survivorship: evaluating ChatGPT's performance in rehabilitation-related queries.

PURPOSE: This study aimed to evaluate the performance of ChatGPT in responding to patient-centered queries related to cancer rehabilitation. It examined the accuracy, completeness, and overall quality of ChatGPT's responses across major domains of cancer rehabilitation from a physical therapy perspective. METHODS: Fifteen representative patient queries covering eight domains of cancer rehabilitati...

Large Language Models for the Differentiation of Benign and Malignant Liver Nodules based on Multimodal Prompts in Liver US Cases.

OBJECTIVE: Large language models (LLMs) that can process both images and text are increasingly being used in radiology. This study aimed to evaluate t...

Machine learning and deep learning models for predicting colorectal cancer metastases: A comprehensive review.

Colorectal cancer (CRC) is a leading cause of cancer-related mortality worldwide, largely due to the development of distant metastases, which is assoc...

Bridging In Silico Design and Experimental Validation: Virtual Screening and In Vitro Assessment of Biomimetic Anticancer Peptides Inspired by Horseshoe Crab Hemolymph Proteins.

BACKGROUND: Colorectal cancer (CRC) remains a leading cause of cancer-related mortality, necessitating the development of more selective and safer the...

Comorbidity Burden and Length of Stay After Myocardial Infarction: A Retrospective Study Using Large Language Model-Assisted Chart Abstraction in a Tertiary Cardiac Hospital.

Patients' length of stay (LOS) during admission for myocardial infarction (MI) represents a closely tracked outcome metric for Cardiology services, wh...

Interpretable multimodal PET/CT-EHR fusion via mixture-of-experts for prognostic stratification in mantle cell lymphoma: a multicenter study.

BACKGROUND: Mantle cell lymphoma (MCL) is a rare, biologically heterogeneous B-cell malignancy with highly variable outcomes. Existing prognostic tool...

Identification and selection of the best artificial intelligence methods developed for detection and diagnosis of breast cancer.

BACKGROUND: Comprehensive identification and prioritization of developed artificial intelligence methods for the detection and diagnosis of breast can...

Accuracy of Deep Learning for Detecting Axillary Lymph Node Metastasis in Breast Cancer: Systematic Review and Meta-Analysis.

BACKGROUND: Axillary lymph node metastasis (ALNM) is an important factor in detecting breast cancer (BC). However, the noninvasive diagnosis of ALNM r...

A multi-cohort evaluation of a curriculum-aligned, oncology-focused chatbot in pharmacy education.

INTRODUCTION: Pharmacy students increasingly rely on generative artificial intelligence (AI) for learning support, yet most available tools remain gen...

Tackling the complexity of cancer with generative models.

The Hallmarks of Cancer framework has played a seminal role in developing our understanding of cancer biology. By design, these hallmarks abstract can...

Cancer cachexia: A tumor-driven disorder of whole-body homeostasis.

Cancer cachexia is a systemic metabolic syndrome driven by tumor-induced disruption of whole-body homeostasis. Characterized by skeletal muscle atroph...

Diagnostic Accuracy of Ultrasound Radiomics for Cervical Lymph-Node Metastasis in Papillary Thyroid Carcinoma: Evidence Predominantly From Chinese Cohorts.

Pre-operative identification of cervical lymph-node metastasis (LNM) guides surgical extent in papillary thyroid carcinoma (PTC) but remains imperfect...

Noninvasive Prediction of Bone Metastasis-Free Survival in Lung Adenocarcinoma Using Interpretable CT-based Deep Learning Model.

RATIONALE AND OBJECTIVES: Preoperatively identifying patients at high risk of bone metastasis (BM) remains challenging in resectable lung adenocarcino...

Optimizing automated sleep stage scoring of 5-s mini-epochs: a transfer learning study.

STUDY OBJECTIVES: Conventional sleep staging relies on 30-s epochs, potentially concealing transient sleep stage intrusion and reducing precision. Bui...

Clinically Localized Prostate Cancer: AUA/ASTRO Guideline Amendment (2026).

PURPOSE: Following completion of the 2025 Update Literature Review (ULR), the American Urological Association (AUA) incorporated new evidence generate...

Artificial intelligence in hepatocellular carcinoma: imaging-based subtyping and prediction of treatment response and prognosis.

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy, accounting for nearly 90% of primary liver cancers worldwide. It is a biol...

Design and first experimental results of an edgeless PET prototype for breast imaging: DeepBreast.

BACKGROUND: Breast cancer causes the largest number of cancer-related deaths among women worldwide. With the aim of improving Positron Emission Tomogr...

Machine Learning-Based Synthetic Computed Tomography Derived From Temporal Bone Magnetic Resonance Imaging.

IMPORTANCE: For diagnostics and presurgical planning in otology, both magnetic resonance imaging (MRI) and computed tomography (CT) are frequently req...

Artificial Intelligence for Identifying Patient-Reported Outcome and Experience Measures in Oncology: Retrospective Cross-Sectional Study Using ClinicalTrials.gov.

BACKGROUND: Traditional health care systems have evolved to increasingly recognize patients' perspectives as key to improving the quality of care, esp...