Oncology/Hematology

Multi-omic biomarker detection in ovarian cancer.

Ovarian cancer remains one of the most lethal gynecologic malignancies, largely because of late-stage diagnosis and the absence of reliable biomarkers for early detection and therapeutic stratification. Recent advances in high-throughput technologies have enabled multi-omics approaches that integrate genomics, transcriptomics, proteomics, metabolomics, and epigenomics to elucidate the comprehensiv...

Prediction of IDH-mutation and 1p19q-codeletion status in adult-type diffuse gliomas using three-class radiomics models.

PURPOSE: To predict the genetic subtypes of adult-type diffuse gliomas with three-class MRI radiomics. MATERIAL AND METHODS: Four hundred and eighty patients with pathologically proved diffuse gliomas from our institution were randomly divided into training set (n = 336) and internal validation set (n = 144) according to a ratio of 7 to 3, and 105 patients from the cancer imaging archive (TCIA) we...

From macroscopic clearance to molecular eradication: paradigm shift and future perspectives in the detecting of residual lesions after transurethral resection of bladder tumors.

INTRODUCTION: Residual lesions after transurethral resection of bladder tumor (TURBT) are a major contributor to recurrence in bladder cancer. Advance...

3D Automated Segmentation of Bronchial Abnormalities on Ultrashort Echo Time MRI: A Quantitative MR Outcome in Cystic Fibrosis.

BACKGROUND: Cystic fibrosis (CF) monitoring relies on computed tomography (CT), but ultra-short echo time MRI (UTE-MRI) offers a radiation-free altern...

Machine learning-assisted photoelectrochemical biosensor based on DNA-AgNCs nanowires for exosomal lncRNA intelligent diagnosis.

BACKGROUND: Exosomal long non-coding RNA (lncRNA) as a burgeoning biomarker, its abnormal expression is closely related to the progression of cancer. ...

Biological multi-omics approaches to next-generation biomarkers in immune-related disorders and malignancies: An overview.

Cancer and autoimmune diseases are major global health challenges characterized by molecular and clinical heterogeneity. Traditional single-analyte bi...

Automated Segmentation of Liver and Liver Tumors with SwinUNETR and UNET Neural Networks on 18F-FDG PET/CT.

OBJECTIVES: To develop and evaluate automated segmentation models for the liver and hepatic tumors on 18F-fluorodeoxyglucose positron emission tomogra...

Integrating lesser omentum adipose CT in dual-phase tumor imaging: A multi-label deep learning framework for preoperative microvascular invasion prediction and survival analysis in hepatocellular carcinoma.

BACKGROUND AND OBJECTIVE: Accurate preoperative prediction of microvascular invasion (MVI) and survival risk is essential for personalized treatment i...

Pathway-Informed Machine Learning Identifies Genetic Predictors of High-Dose Methotrexate-Induced Mucositis in Pediatric Acute Lymphoblastic Leukemia.

High-dose methotrexate for pediatric cancer treatment is frequently associated with mucositis, which can lead to delayed or discontinued treatment and...

Understanding unrealized trial enrollments following patient-to-trial matching with large language models.

BACKGROUND: Clinical trials are essential for advancing cancer care, but identifying eligible patients in surgical clinics can be challenging due to t...

Using machine learning to predict clinical remission with exclusive enteral nutrition in pediatric Crohn disease.

OBJECTIVES: Exclusive enteral nutrition (EEN) is a first-line treatment for induction of remission in luminal pediatric Crohn disease (pCD). However, ...

Artificial intelligence powered mobile health apps for skin cancer detection: current challenges and a systems thinking approach for improved public health outcomes in low- and middle-income countries.

Artificial intelligence (AI) powered mobile health (mHealth) apps are emerging as vital self-triage tools for skin cancer detection. By utilizing smar...

Mapping Knowledge Landscapes and Emerging Trends in Contrast-Enhanced Ultrasound for Breast Cancer: A Bibliometric and Visualization Analysis.

Breast cancer remains a leading threat to women's health worldwide and reducing mortality hinges on early detection. Contrast-enhanced ultrasound (CEU...

Anomaly changes in the functional connectome of post-operative neurosurgical patients: A case series.

PURPOSE: The use of neuronavigation with superimposed mapping tools has enabled visualization of key fiber tracts and improved peri-operative planning...

Three-dimensional surface scanning for registration in stereotactic neurosurgery: a cadaveric feasibility study.

OBJECTIVE: Achieving submillimetric accuracy in stereotactic neurosurgery remains critical for safely targeting deep brain structures. Current workflo...

An Explainable Deep Model for Risk Scoring and Accurate Radionecrosis Identification Following Brain Metastasis Stereotactic Radiosurgery.

PURPOSE: As survival improves for patients with brain metastases (BM), distinguishing local recurrence (LR) from radionecrosis (RN) is a growing neuro...

Prediction of Lung Metastasis in Breast Cancer Patients Using Machine Learning Classifiers.

Breast cancer is the most common cancer among women, and metastasis to the lung is associated with poor prognosis. Reliable biomarkers for predicting ...

Digital pathology-based prognostic model for hepatocellular carcinoma: Integrating pathomics signatures with clinical parameters for recurrence prediction and biological interpretation.

BACKGROUND: Hepatocellular carcinoma (HCC) remains a therapeutic challenge due to high post-resection recurrence rates and heterogeneous outcomes. We ...

Turmeric extracellular vesicles-derived "all-in-one" nanoagent enables full-cycle synergistic immunomodulation of lung cancer.

Lung cancer's metastatic propensity and recurrence prevalence necessitate innovative immunotherapy strategies beyond conventional single-mode regulati...

Diagnosis of head and neck cancer by AI-based tumor-educated platelet RNA profiling of liquid biopsies.

Over 95% of head and neck cancers are squamous cell carcinoma (HNSCC). HNSCC is mostly diagnosed late, causing a poor prognosis despite the applicatio...