Oncology/Hematology

A prognostic model based on nucleotide metabolism genes in osteosarcoma.

Osteosarcoma typically arises during adolescence, posing a significant challenge. Despite comprehensive treatment strategies encompassing surgery, radiation therapy, and chemotherapy, which can notably enhance long-term survival rates among osteosarcoma patients, the 5-year survival rate for metastatic cases remains discouragingly low. Consequently, early diagnosis and prompt intervention are para...

Dual-band graphene-based THz MIMO antenna for 6G-enabled biomedical application using supervised regression machine learning validation.

The exponential increase in wireless data traffic and the growing demand for biomedical sensing have driven the advancement of sophisticated antenna technologies, particularly within the terahertz (THz) frequency range. This research presents an innovative graphene-based microstrip patch antenna featuring a slotted design and MIMO configuration, specifically designed for the high-speed needs of 6G...

A multimodal explainable ai framework to assist in the differential diagnosis of head and neck reactive follicular hyperplasia and follicular lymphoma: an international multicentre study.

The differential diagnosis between reactive follicular hyperplasia (RFH) and follicular lymphoma (FL) in head and neck tissues represents a diagnostic...

Synthetic inducible bacteria normalize the microenvironment of refractory tumors, potentiating checkpoint inhibitor responses.

Immunotherapy has transformed cancer treatment but remains ineffective in many solid tumors, largely due to the immunosuppressive tumor microenvironme...

Overexpression of NMNAT3 suppresses melanoma progression by reprogramming NAD⁺ metabolism.

BACKGROUND: Melanoma represents a highly aggressive and metastatic form of malignant skin cancer. that remains challenging to treat clinically. Tumor ...

Imaging of Small Cell Lung Cancer: An Updated Overview of Current and Emerging Applications.

Small cell lung cancer (SCLC) is an aggressive pulmonary neuroendocrine carcinoma characterized by rapid progression and early metastasis. Despite rec...

Impact of Artificial Intelligence-Assisted Endoscopy on Screening for Upper Gastrointestinal Cancer in a Large-Scale Health Screening Facility.

OBJECTIVES: Artificial intelligence (AI)-assisted endoscopy has been developed for the early detection of upper gastrointestinal cancer; however, its ...

Feasibility of No-Code Deep Learning for Diagnosing Bone Metastasis in Bone Scans: A Comparative Study of Teachable Machine and ResNet.

This study explored the feasibility of developing a model that can diagnose positive and negative bone metastasis from bone scan images using Teachabl...

A machine learning framework combining cfDNA fragmentomics and serum biomarkers for early ovarian cancer detection.

BACKGROUND: Ovarian cancer (OC) is a leading cause of cancer-related mortality in women, largely due to the lack of effective strategies for early det...

Two-staged CT-based radiomics model in characterising early-stage ovarian carcinoma and benign ovarian masses.

BACKGROUND: Characterisation of CT detected ovarian masses is challenging with overlapping imaging features, unreliable biomarker or clinical presenta...

Deciphering the predictors of endometrial nonbenign lesions in asymptomatic postmenopausal women via explainable machine learning.

OBJECTIVES: Timely identification of endometrial nonbenign lesions led to improved outcomes, but there was a lack of effective predictive models for a...

Interactive active learning for literature screening: finetuning GPT with DeepSeek reasoning for cross-domain generalization.

OBJECTIVE: Automated literature screening in biomedical research is often hindered by domain shifts and scarcity of labeled data, which limit model ac...

Multiparametric MRI-based Deep Learning and Radiomics for Evaluating Lymph Node Metastasis in Early-Stage Cervical Cancer.

Purpose To develop a multiparametric MRI-based radiomics model and deep learning-radiomics (DLR) fusion model for preoperative prediction of lymph nod...

Evaluating an AI-driven Triaging Workflow for MRI-based Clinically Significant Prostate Cancer Diagnosis: A Simulation Study.

Purpose To simulate an artificial intelligence (AI)-driven triaging workflow in which an AI system, using high-confidence thresholds, assesses a subse...

Investigation of the Accuracy and Contributing Factors of AI-Based Diagnosis of Urothelial Carcinoma in Canine Abdominal Radiography.

Urothelial carcinoma (UC) is a highly malignant urinary cancer of the transitional epithelium in dogs. Recent advances in artificial intelligence (AI)...

The Prognostic and Biological Value of PGF-Based H&E Pathomics in Hepatocellular Carcinoma.

PURPOSE: Placental growth factor (PGF) is associated with the progression of hepatocellular carcinoma (HCC), but current research on this relationship...

A transformer-based patient-agnostic tumor motion tracking model (TransTracking): A feasibility study in radiotherapy for lung cancer.

BACKGROUND: Accurate and real-time localization of thoracic tumor targets is essential for effective radiation therapy. Recently, Transformer architec...

Deep Learning Model Based on Tumor and Visceral Adipose Tissue CT Features for Predicting Peritoneal Metastasis Risk after Radical Gastrectomy in Serosa-Invasive Gastric Cancer.

Purpose To develop and validate a deep learning model integrating tumor and visceral adipose tissue (VAT) CT scan features with clinical indicators to...

An XGBoost-Based Multicenter Model for Predicting HBV-Related Hepatocellular Carcinoma: Development and Validation.

BACKGROUND: The 5-year survival rate for hepatocellular carcinoma (HCC) is stage-dependent, yet existing models lack accuracy in predicting hepatitis ...

[Staging of middle ear cholesteatoma surgery and its value for clinical decision-making].

Middle ear cholesteatoma is characterized by squamous epithelial accumulation within the middle ear cavity, which can lead to severe complications suc...