Latest AI and machine learning research in other cancers for healthcare professionals.
Given the rising incidence of bone metastases, computed tomography is widely used worldwide as the initial imaging modality for their detection. Accurate diagnosis of bone metastases demands comprehensive evaluation, yet divergent interpretations among specialists can result in diagnostic discrepancies. In clinical practice, precision diagnosis of bone metastases necessitates multidisciplinary col...
BACKGROUND: Pancreatic cancer (PC) is a highly malignant tumor with increasing incidence, mortality, and a low five-year survival rate. Mitochondrial metabolic reprogramming plays a crucial role in tumor development, but the molecular mechanisms in different cell subpopulations of PC remain unclear. This study aims to integrate single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq to explore mit...
BACKGROUND: Colorectal cancer (CRC) is one of the most common malignancies worldwide and remains a major clinical challenge, underscoring the urgent n...
PURPOSE: The purpose of this study was to evaluate whether explicitly modeling diabetes mellitus (DM) without diabetic retinopathy (DR) as its own sta...
Tumor heterogeneity remains a major barrier to effective cancer therapy, driving the need for novel biomarkers and targeted strategies. A bibliometric...
Vasculogenic mimicry (VM), a novel endothelial-independent blood perfusion pathway, is linked to advanced stage and poor prognosis in esophageal squam...
Predictive tools made possible by advances in machine learning techniques may help clinicians make more accurate decisions about who should be allocat...
The incremental value of multiparametric MRI (mpMRI) in prostate cancer staging has been increasingly recognized, with the accumulated literature indi...
PURPOSE: Antibody-drug conjugates (ADC) targeting trophoblast cell surface antigen 2 (TROP-2) and cMET are entering clinical trials in non-small cell ...
UNLABELLED: Pancreatic ductal adenocarcinoma (PDAC) evolves through precursors, yet the protein programs governing early progression remain poorly def...
Clusmann and colleagues developed PRE-Screen-HCC, an interpretable machine learning framework that leverages multimodal clinical data from 2 populatio...
PURPOSE: Joint space narrowing (JSN) in rheumatoid arthritis (RA) can progress even during clinical remission. Conventional imaging lacks sensitivity ...
Oral leukoplakia (OLK) is the most common oral potentially malignant disorder and carries a lifetime risk of transformation to oral squamous cell carc...
BACKGROUND AND PURPOSE: Image preprocessing is an essential, though often overlooked, part of machine learning, and it is unclear how preprocessing te...
Neuropilin-1 (NRP1) is a key mediator of tumor metastasis and progression by controlling cancer cell migration, angiogenesis, and tumor immune respons...
This single-center retrospective study developed and internally validated a two-dimensional deep learning model based on cone-beam computed tomography...
We present a retrospective dataset of contrast-enhanced T1-weighted magnetic resonance imaging scans from 140 patients with brain metastases who under...
OBJECTIVES: This study proposes a deep convolutional neural network model that integrates B-mode and D-mode ultrasound images to classify metastatic l...
BACKGROUND: Ribosome biogenesis is involved in the progression of hepatocellular carcinoma (HCC), but the specific mechanisms and diagnostic values of...
A complete human sleep consists of multiple states, each of which has its own unique and typical characteristics. A clear definition of these states l...