Oncology/Hematology

Artificial Intelligence-Driven MRI for Cervical Nodal Metastasis Detection in Oral Squamous Cell Carcinoma: A Hierarchical Meta-Analysis of Diagnostic Accuracy.

BACKGROUND: Artificial intelligence (AI) applied to magnetic resonance imaging (MRI) may improve detection of cervical lymph node metastases in oral squamous cell carcinoma (OSCC) but is heterogeneous. METHODS: A systematic review identified observational studies (from 2000) evaluating AI-based MRI in adults with histopathologically confirmed OSCC. Risk of bias was assessed with QUADAS-AI. Diagnos...

Multi-omics investigation of per- and polyfluoroalkyl substances in lung adenocarcinoma: comprehensive network toxicology, machine learning and molecular docking experiments.

Growing concerns regarding per- and polyfluoroalkyl substances (PFAS) as pervasive environmental contaminants have prompted increasing scrutiny regarding their potential contributions to pulmonary diseases. Therefore, this study specifically investigates their implications in lung adenocarcinoma (LUAD) pathogenesis. We utilized the Comparative Toxicogenomics Database (CTD), GeneCards, and OMIM dat...

Machine learning-based integration develops a novel lysosome-related prognostic signature associated with prognosis and immune infiltration landscape in acute myeloid leukemia.

BACKGROUND: Lysosomes are essential for intracellular degradation and recycling, and changes in their function significantly contribute to tumor growt...

Machine learning applications in the detection and treatment of esophageal cancer.

Esophageal cancer (EC) is a gastrointestinal malignancy associated with a poor prognosis worldwide. It is characterized by an insidious onset, marked ...

From Magnetic Resonance Imaging Radiomics to the Prediction of Regional Nodal Metastasis in Laryngeal Cancer.

OBJECTIVE: To investigate the potential of magnetic resonance imaging (MRI) radiomics-based machine learning (ML) models in predicting local lymph nod...

Improved Detection of Lentigo Maligna with AI-Assisted Dermoscopy: A Reader Study in Facial Pigmented Lesions.

BACKGROUND: Differentiating lentigo maligna (LM) from benign facial pigmented lesions remains difficult due to substantial clinical and dermoscopic ov...

AI-Assisted HER2 Scoring in Breast Cancer: Diagnostic Agreement and Understanding Discordance.

PURPOSE: With trastuzumab deruxtecan demonstrating clinical benefit in HER2-low and ultralow breast cancer, precise discrimination at the lowest end o...

Integrated bioinformatics, machine learning, and experimental validation identify a four-gene diagnostic signature for cervical cancer associated with PI3K/AKT signaling.

Early and accurate diagnosis remains a major challenge in cervical cancer management. This study aimed to identify reliable diagnostic biomarkers for ...

Identification and validation of BLK and OSBPL10 as diagnostic and prognostic biomarkers for nasopharyngeal carcinoma through machine learning algorithms.

Despite substantial advances in radiotherapy and chemotherapy for nasopharyngeal carcinoma (NPC), a subset of patients still develops metastasis or re...

APASA: adaptive selection of informative peritumoral regions for improved automated cancer lesion analysis.

Precise cancer lesion analysis in medical imaging critically depends on the accurate definition of regions of interest (ROIs), which directly influenc...

Metabolic pathway signatures define prognostic subtypes of lung adenocarcinoma.

Metabolic reprogramming is a core hallmark of cancer, yet how it contributes to the clinical heterogeneity of lung adenocarcinoma (LUAD) remains poorl...

AI-Based Opportunistic CT Risk Assessment Using TotalSegmentator in Osteoporotic Vertebral Fractures.

Osteoporotic vertebral fractures impair quality of life and increase both morbidity and mortality, yet they are largely preventable. Routine CT examin...

Semi-automatic mask guidance enhances 3D tumor segmentation in medical imaging.

BACKGROUND: Accurate tumor segmentation is essential for early diagnosis, treatment planning, and prognostic evaluation. Although manual annotation ca...

[Current status and progress of prognostic evaluation in marginal zone lymphoma].

Marginal zone lymphoma (MZL) is an indolent B-cell non-Hodgkin lymphoma with marked heterogeneity. Currently, histological subtype, clinical stage, bi...

Comparative 10-year performance of mammography artificial intelligence, polygenic, and clinical breast cancer risk models in the Kaiser Permanente Research Bank.

BACKGROUND: We compared performance across 3 breast cancer risk domains-clinical, polygenic, and mammography artificial intelligence-alone and in comb...

Innovative screening for OSAS in patients with head and neck cancer using the apneal application: Protocol for a prospective single-centre study.

INTRODUCTION: OSAS is a common yet underdiagnosed condition, particularly among patients with head and neck cancers (HNC). Anatomical changes caused b...

Mechanobiology of the tumor microenvironment: a review of therapeutic interactions and in vitro elasticity measurement techniques.

The stiffness of the extracellular matrix (ECM) regulates cellular behavior, influencing tumor progression and therapeutic resistance. In cancer, aber...

Development and validation of a machine learning-based postoperative staging system for hilar cholangiocarcinoma: a retrospective single-center cohort study.

BACKGROUND: Hilar cholangiocarcinoma (HCCA) is a malignant tumor at the hepatic hilum with poor prognosis and survival despite surgical resection. Whi...

Integrating neurobiological markers to prospectively predict adolescent non-suicidal self-injury and suicide attempts: a machine learning approach.

BACKGROUND: Suicide attempts (SA) and non-suicidal self-injury (NSSI) are closely related phenomena, both common in adolescent clinical samples. This ...

Single-cell RNA sequencing in ovarian cancer: decoding the tumor microenvironment for personalized therapy.

Ovarian cancer (OC) remains a leading cause of mortality among gynecological malignancies, largely due to profound inter- and intra-tumoral heterogene...