Oncology/Hematology

Smartphone-Based Proactive Self-Screening for Ocular Surface Malignancies: A Nonrandomized Clinical Trial.

IMPORTANCE: Ocular surface malignancies pose risks to vision and survival yet are frequently misdiagnosed as benign lesions because of their subtle presentation and the lack of widely accessible screening tools, potentially resulting in treatment delays and the need for extensive surgical intervention. OBJECTIVE: To develop and validate a smartphone-based, media-facilitated artificial intelligence...

Advancing Gastrointestinal Cancer Risk Prediction With Patient-Centered Machine Learning: Machine Learning Modeling Study.

BACKGROUND: Gastrointestinal (GI) cancers are a significant health concern in South Korea. Recently, machine learning (ML) models have emerged as powerful tools to support early screening efforts and identify people at risk before disease onset. However, the low incidence of GI malignancies in prospective cohorts leads to severe class imbalance, often causing ML models to favor the majority "healt...

Early Immunological Biomarkers for Personalized Treatment Selection in Severe COVID-19: Post Hoc Machine Learning Analysis of a Randomized Clinical Trial.

BACKGROUND: Severe COVID-19 is a global health concern despite continuous vaccination campaigns because current therapies, such as dexamethasone and r...

Radiation dose-aware sinogram knowledge library transformer with feature modulation for low-dose medical image segmentation.

Low-dose computed tomography (LDCT) and low-dose positron emission tomography (LDPET) enable shorter acquisition times and lower radiation exposure. H...

Novel technologies for gastrointestinal cancer detection: a systematic review and meta-analysis of diagnostic accuracy.

INTRODUCTION: Gastrointestinal (GI) cancers account for a quarter of all cancers and one-third of cancer-related deaths worldwide. Novel diagnostic ap...

Plasma signals of lung tumor promotion for molecular cancer prevention.

Predicting lung cancer risk would enhance prevention trials. Although the Canakinumab Anti-inflammatory Thrombosis Outcome Study (CANTOS) trial demons...

Diagnostic yield and cost of three-level H&E sectioning in prostate biopsies.

AIM: The traditional three-level H&E sectioning protocol for prostate biopsies was developed for ultrasound-guided systematic sampling and predates le...

[State of the art and innovations in breast cancer prevention and screening strategies].

Breast cancer is the most common cancer among women, and its incidence is increasing, particularly in France, due to changes in lifestyle and exposure...

Multi-scale computational analysis of monoacylglycerol lipase inhibition as a new therapeutic strategy for hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) remains one of the most critical global health challenges, particularly in connection to metabolically linked diseases ...

Comprehensive multi-omics analysis identifies cancer subtypes and prognostic signatures of hepatitis B virus-associated hepatocellular carcinoma.

Hepatitis B virus-associated hepatocellular carcinoma (HBV-HCC) is a heterogeneous malignancy with poor prognosis, necessitating refined classificatio...

Label-free interferometry platform for drug response profiling of bioprinted tumor organoids at single-organoid resolution.

Organoids have become mainstay tools for drug discovery and personalized medicine. High-throughput imaging readouts for drug screening of tumor organo...

An interpretable ultrasound-based deep learning system for early breast cancer in a Chinese population.

OBJECTIVES: Current deep learning models for early breast cancer lack interpretability and multimodal integration, limiting their clinical acceptance....

Construction and validation of a machine learning-based prediction model for social isolation in patients with colorectal cancer after stoma surgery.

OBJECTIVE: To investigate the current status and influencing factors of social alienation in patients with enterostomy after colorectal cancer surgery...

Federated MobileNetV2 with ensemble meta-learning for privacy-preserving brain tumor classification.

The identification of brain tumors from MRI images is very crucial for the selection of an appropriate treatment. However, the existing solution has i...

SpatioCell: deep integration of histology and spatial transcriptomics for profiling the cellular microenvironment at single-cell level.

Spatial transcriptomics (ST) is a powerful assay for capturing gene expression in tissues. However, due to inherent limitations of spatial resolution,...

Integrative Network Toxicology and Machine Learning Identify AKR1C3 as a Candidate Functional Target of Cypermethrin in Colorectal Cancer.

The potential contribution of foodborne pesticide residues to colorectal cancer (CRC) remains insufficiently understood. In this study, we integrated ...

Toward a Synthetic Data Revolution: Diffusion Model-Enhanced Hepatocellular Carcinoma Prediction in Steatotic Liver Disease.

AIM: Steatotic liver disease (SLD) encompasses a heterogeneous spectrum with varying risks of hepatocellular carcinoma (HCC). Limited sample sizes lim...

Extracellular Vesicles in Exhaled Breath Condensate as Emerging Biomarkers in Lung Cancer.

Exhaled breath condensate (EBC) has emerged as a noninvasive liquid biopsy medium that captures aerosolized material from the respiratory tract and ma...

Impact of nanocarrier mediated drug delivery systems: a deep dive into therapeutics and clinical management of breast cancer.

Breast cancer (BC) is the most frequently diagnosed malignancy and the leading cause of cancer-related death among women worldwide. The therapeutic li...

Externally Tested AI Models for Malignancy Classification of Lung Nodules at Chest CT: A Systematic Review and Meta-Analysis.

Purpose To evaluate the pooled diagnostic accuracy of externally tested AI models for malignancy classification of lung nodules on chest CT. Materials...