Oncology/Hematology

Fusing data from CT deep learning, CT radiomics and peripheral blood immune profiles to diagnose lung cancer in a cohort of patients experiencing symptoms.

BACKGROUND: Lung cancer is the leading cause of cancer-related deaths. Diagnosis at late stages is common due to the largely non-specific nature of presenting symptoms contributing to high mortality. There is a lack of specific, minimally invasive low-cost tests to screen patients ahead of the diagnostic biopsy. METHODS: 344 patients experiencing symptoms from the lung clinic of Lister hospital su...

Evaluating the role of the main pancreatic duct in intraductal papillary mucinous neoplasm grading: A multi-structure radiomics-based machine learning approach.

PURPOSE: The purpose of this study was to evaluate the contribution of radiomics features extracted from various pancreatic structures on computed tomography (CT) images, including the main pancreatic duct and cystic lesion, for predicting the pathological grade of intraductal papillary mucinous neoplasms (IPMNs) using machine learning models. MATERIALS AND METHODS: A retrospective study using pre...

Nanoengineering of Exosomal Surfaces for Precision Targeting and Payload Delivery at the Molecular Level.

Exosomes, nano-sized extracellular vesicles secreted by almost all cell types, have emerged as biologically compatible vehicles for targeted drug deli...

Two-Step Semiautomated Classification of Choroidal Metastases on MRI: Orbit Localization via Bounding Boxes followed by Binary Classification via Evolutionary Strategies.

BACKGROUND AND PURPOSE: The choroid of the eye is a rare site for metastatic tumor spread, and as small lesions on the periphery of brain MRI studies,...

Deep Learning Integration of Endoscopic Ultrasound Features and Serum Data Reveals LTB4 as a Diagnostic and Therapeutic Target in ESCC.

BACKGROUND: Early diagnosis and accurate prediction of treatment response in esophageal squamous cell carcinoma (ESCC) remain major clinical challenge...

Dual-Parallel Artificial Intelligence Framework for Breast Cancer Grading via High-Intensity Ultrasound and Biomarkers.

BACKGROUND: Accurate and noninvasive breast cancer grading and therapy monitoring remain critical challenges in oncology. Traditional methods often re...

AI portal tract detection and characterisation for a regional analysis of steatosis and inflammation in MASLD, MASH and AIH.

AIMS: Annotation of liver biopsies for disease staging is increasingly aided by digital pathology; however, existing systems do not quantify inflammat...

Histopathological diagnosis of Ovine Pulmonary Adenocarcinoma (OPA) based on ensemble model.

Strategies of AI-Driven CAR-T Cell Therapy Towards Solid Tumours.

Chimeric antigen receptor (CAR)-T cell immunotherapy shows significant success in hematologic malignancies. However, it faces critical challenges in s...

Bacterial Outer Membrane Vesicles in Potentiating Cancer Vaccines: Progress and Prospects.

Cancer immunotherapy is increasingly moving toward personalized, precision-based strategies, with cancer vaccines emerging as a promising approach to ...

A Unified Machine Learning Model for Relapse Prediction in Clinical Stage I Testicular Cancer.

BACKGROUND: Approximately one-fourth of patients with clinical stage I testicular cancer relapse. For decades, risk stratification has been based on d...

Intelligent identification and targeted intervention of GRP75-caused drug resistant hepatocellular carcinoma, a study based on radiomics, machine learning, and molecular pharmacology.

BACKGROUND: Tumor heterogeneity mediated drug resistance was a core clinical challenge to improve the prognosis of patients with advanced hepatocellul...

Assessment of Predictive Factors That Shorten Duration of Treatment in Patients With Multiple Myeloma Using AI: Real-World Longitudinal Study Using Data From Medical Data Vision Claims Database.

BACKGROUND: With the availability of newer therapies, the duration of therapy (DoT) shortens with each increasing line of treatment in Japanese patien...

Post-treatment infection prediction in CLL using domain adaptation of lymphoma electronic health records.

BACKGROUND AND PURPOSE: Infections are the leading cause of morbidity and mortality in patients with chronic lymphocytic leukemia (CLL) and occur duri...

Integration of Raman tweezers and machine learning for label-free single-cell characterization of endometriosis cells.

Endometriosis occurs when endometrial tissue grows outside the uterus, affecting millions of women worldwide. Despite extensive research, its cellular...

MRI-based habitat radiomics for assessing synchronous metastatic risk in renal cell carcinoma: a multicenter study.

PURPOSE: To explore the role of MRI-based habitat radiomics in assessing the metastatic status of renal cell carcinoma (RCC). METHODS: This study retr...

Impact of Transfer Learning on Convolutional Neural Networks for Odontogenic Tumor Diagnosis.

OBJECTIVE: This study aimed to evaluate the coherence between data heterogeneity and model complexity by comparing seven convolutional neural network ...

ASO Visual Abstract: CT-Based Prediction of Visceral Pleural Invasion in Lung Adenocarcinoma ≤ 3 cm: Enhancing Deep Learning Specificity by Waiving Chest Wall Information.

Identifying Transdiagnostic Predictors of Depression Across Psychoses: Informing Stratified Antidepressant Treatments.

INTRODUCTION: Depression frequently co-occurs with psychosis and is associated with poor outcomes. Early identification of patients at risk of persist...

Screening for Clinically Significant Nephrolithiasis Based on Simple Health Checkup Clinical and Urine Parameters in General Populations: Multicenter Machine Learning Study.

BACKGROUND: Nephrolithiasis affects approximately 15% of the population and often remains undetected in asymptomatic individuals. Current diagnostic a...