Other Cancers

Predicting TP53 Biomarkers from Whole Slide Images across Human Solid Tumors Using Weakly Supervised Learning.

Accurate molecular profiling from routine histopathology slides could transform clinical oncology. A Vision Transformer (ViT)-based model was developed to jointly predict the TP53 biomarker, detect 32 solid tumor types, and predict survival directly from whole slide images (WSIs). Over 11,000 primary tumor data were retrieved from the Pan-Cancer Atlas, along with corresponding somatic mutation, RN...

Fusion of MRI-radiomics and clinical features to improve pathological T-stage prediction of rectal cancer: a multicenter study.

BACKGROUND: Developing a rational model for precise preoperative staging of rectal cancer using magnetic resonance imaging is crucial for improving the therapeutic effect and prognosis of patients. To investigate the feasibility and efficacy of a T2-weighted imaging (T2WI) based radiomics model combined with clinical features for preoperative T1-2/T3 staging prediction in rectal cancer. METHODS: A...

Wavelet Spectrum in a Multi-Channel Network May Reduce Biopsy Rates on Diagnosis of Breast Tumors with BI-RADS Category 4a or Higher.

OBJECTIVES: BI-RADS 4a+ breast tumors have a high rate of unnecessary biopsies due to ambiguous diagnostic features. This study aims to develop and ev...

A Single-Cell Guided Machine Learning Model Predicts Response to Immune Checkpoint Inhibitors in Gastric Cancer.

Resistance to immune checkpoint inhibitors is a major clinical obstacle in the treatment of gastric cancer. Identifying drug-resistant cell population...

Functional Imaging in Hereditary Endocrine Neoplasms: Evolving Modalities and Clinical Implications.

Hereditary endocrine neoplastic syndromes require structured, lifelong surveillance owing to their multisystem involvement, variable penetrance, and h...

Deep learning applications in cancer treatment Prediction: Comprehensive research foundation for systematic review and Meta-Analysis.

Deep learning has rapidly emerged as a transformative technology in oncology, offering new capabilities in treatment response prediction and personali...

Machine Learning-Driven Prognostic Modeling in Head and Neck Adenoid Cystic Carcinoma: A Retrospective Cohort Study.

INTRODUCTION: Adenoid cystic carcinoma (ACC) of the head and neck is a rare malignancy characterized by perineural invasion, local recurrence, and dis...

Multimodal assessment of minimally conscious state and cognitive motor dissociation in neurocritical care: A critical review.

Minimally conscious state (MCS) is characterized by inconsistent but clearly discernible clinical and behavioral evidence of consciousness. Cognitive ...

Label-free classification of breast cancer subtypes in ex vivo human tissues using Raman spectroscopy and machine learning.

Breast conserving surgery (BCS) aims to excise breast tumors whilst preserving breast-related quality of life, but is complicated by the challenge of ...

Computational pathology model to predict recurrence-free survival in NMPUC patients on BCG-therapy.

Urothelial carcinoma, predominantly appearing as non-muscle-invasive papillary urothelial carcinoma (NMIPUC), exhibits wide clinical variability. Accu...

A lightweight ResNet50V2-ECA model for renal cell carcinoma grading: efficiency, calibration, and state-of-the-art performance.

Accurate International Society of Urological Pathology (ISUP)-grade classification of renal cell carcinoma (RCC) is challenging due to subtle histopat...

Integrative single-cell and spatial transcriptomics with machine learning identify a Luminal-inflam malignant program and reveal an RPN1-PERK UPR vulnerability in triple-negative breast cancer.

Triple-negative breast cancer is marked by extensive cellular heterogeneity and limited availability of actionable targeted treatments, which contribu...

PathTIGR: A pathway topology-informed graph representation learning framework for immunotherapy response prediction.

Immunotherapy has revolutionized cancer treatment, yet substantial inter-patient response heterogeneity limits therapeutic benefit to specific patient...

Swin UNETR-based prediction of [68Ga]Ga-FAPI-46 PET/CT dose rate maps in cancer patients: quantitative comparison with [18F]FDG PET/CT.

BACKGROUND: Fibroblast activation protein (FAP) is a promising theranostic target due to its high stroma expression in numerous malignancies. This stu...

Caregiver Preferences for AI-Supported Telemedicine in Pediatric Palliative Care: A Discrete Choice Experiment.

BackgroundAsynchronous telemedicine may support home-based pediatric palliative care (PPC) by improving access to professional guidance and reducing c...

Machine learning for predicting liver metastasis in colorectal cancer.

AIM: To evaluate the performance of machine learning models in predicting liver metastasis in colorectal cancer (CRC) patients using the SEER database...

Identifying PLAU as a shared pathogenic gene in type 2 diabetes and bladder urothelial carcinoma through integrated transcriptomic analysis and machine learning for diagnostic and therapeutic value.

Type 2 diabetes mellitus (T2DM) and bladder urothelial carcinoma (BLCA) are two kinds of diseases that seriously threaten human health. Their pathogen...

Development and validation of a machine learning-based model for predicting delirium risk in postoperative brain tumor patients in the Intensive Care Unit.

OBJECTIVE: This study aimed to clarify the incidence and influencing factors of delirium in ICU patients after brain tumor surgery, construct and vali...

Prompt-directed ambient artificial intelligence for automated multidisciplinary tumor board documentation.

BACKGROUND: Tumor board documentation is challenging due to complexity of multidisciplinary input. Ambient artificial intelligence (AI) for medical di...

Quantification of Histotripsy Dosage Using Machine Learning-Enhanced Ultrasound Imaging Analysis: Correlation with Histological Outcomes.

RATIONALE AND OBJECTIVES: Histotripsy is a noninvasive ultrasound therapy that mechanically disrupts target tissue through controlled acoustic cavitat...