Oncology/Hematology

PanMB2-Net: a deep learning framework for preoperative MB2 canal risk assessment on panoramic radiographs.

OBJECTIVES: This study aimed to develop and validate a clinically motivated artificial intelligence framework for preoperative risk assessment of the second mesiobuccal (MB2) canal in maxillary first molars using panoramic radiographs. MATERIALS AND METHODS: A total of 388 panoramic radiographs were retrospectively collected. Stage 1 used YOLOv5 to localize maxillary first molars and crop tooth-le...

Circulating NSUN6 serves as a prognostic biomarker for early metastasis in HCC via hippo pathway modulation.

BACKGROUND: Portal vein tumor thrombus is a lethal complication of HCC for which effective biomarkers are urgently needed. METHODS: Through proteomic profiling, functional and mechanistic assays, and machine learning-based evaluation of serum NSUN6 in 472 HCC patients with external validation (n = 98), we characterized an epitranscriptomic regulator of HCC metastasis. RESULTS: NSUN6 was downregula...

The evolving bioinformatic approaches to identifying genetic targets of promise in cancers.

INTRODUCTION: The search for actionable genetic targets in cancer has evolved substantially over the past decade. Earlier approaches were focused on s...

Prediction of Central Lymph Node Metastasis in Papillary Thyroid Carcinoma Using Multi-Ultrasound Radiomics of Intratumoral and Peritumoral Regions.

OBJECTIVE: The aim of this study was to integrate multimodal intratumoral and peritumoral ultrasound radiomic features with clinical data to construct...

Therapeutic hybrid intelligence with neural and knowledge-based expert reasoning for SRS (THINKERS): an AI model for meningioma.

BACKGROUND: Prescription dose selection for intracranial meningiomas treated with stereotactic radiosurgery remains guided by tumor volume, anatomical...

Clinical target volume radiomics from planning CT for pretreatment response prediction  in rectal cancer undergoing chemoradiotherapy.

PURPOSE: Response to neoadjuvant chemoradiotherapy (nCRT) in rectal cancer remains heterogeneous. This exploratory study evaluated whether radiomics f...

Deep learning-based automated assessment of alveolar bone loss in CBCT for periodontitis.

OBJECTIVES: This study aimed to develop and validate a CBCT-based automated system for assessing radiographic alveolar bone loss (RBL) to improve the ...

Is adenosine signalling entering the precision medicine era? From receptor pharmacology to patient stratification.

Over the past three decades, adenosine signalling has emerged as a fundamental regulatory system controlling immune responses, tissue homeostasis, met...

Metabolic signatures of triple-negative breast cancer.

Triple-negative breast cancer (TNBC), being one of the most aggressive subtypes of breast malignancies, is characterized by poor prognosis and limited...

Interpretable machine-learning survival prediction of breast cancer prognosis from lifestyle factors: evidence from UK biobank.

BACKGROUND: Understanding how lifestyle habits influence breast cancer survival is crucial for improving long-term outcomes and guiding individualized...

Deep learning reveals FLAD1-mediated mitochondrial metabolic reprogramming in hypoxic tumors.

Hypoxia, a hallmark of solid tumors, drives malignant progression and represents a major therapeutic challenge. Metabolic reprogramming induced by hyp...

Identifying Cancer Driver Genes Based on Vision Transformer and Hierarchical Feature Fusion Module.

Cancer is a global public health problem that poses a huge threat to human life and health. The identification of cancer driver genes helps to discove...

Development and Validation of a Multimodal-Multitask Deep Learning Approach for Estimating Late Distant Recurrence Risk in HR-Positive Early Breast Cancer.

Late distant recurrence (DR) remains a persistent risk in hormone receptor-positive (HR+) early breast cancer after completion of 5 years of endocrine...

Ovarian Cancer Diagnosis and Chemoresistance Prediction Model Based on cfRNA Molecular Signature.

BACKGROUND: Ovarian cancer (OVCA) is a common and highly aggressive gynecologic malignancy often diagnosed at advanced stages. Approximately 30% of pa...

Radiation-induced erectile dysfunction in prostate cancer: A systematic review of pathophysiology, clinical radiobiology, and predictive modeling.

BACKGROUND: Radiation-induced erectile dysfunction (RIED) remains one of the most prevalent and distressing late toxicities among prostate cancer surv...

Spatial architecture of tertiary lymphoid structures represents an independent prognostic dimension in hepatocellular carcinoma.

BACKGROUND AND AIMS: Tertiary lymphoid structures (TLS) are associated with heterogeneous outcomes in hepatocellular carcinoma (HCC), but whether thei...

Identification of genomic features that uniquely impact estrogen receptor alpha binding and its effects on gene expression in endometrial cancer.

Estrogen receptor 1 (ESR1) is an established oncogenic transcription factor in breast and endometrial cancer; however, more is known about the mechani...

Integrating CT Radiomics and Machine Learning for Preoperative Assessment of STAS Grading and Prognostic Stratification in Lung Adenocarcinoma.

RATIONALE AND OBJECTIVES: The distance of spread through air spaces (STAS) dissemination is associated with prognosis in lung adenocarcinoma (LUAD). T...

A Machine-Learning Model Using Pre-treatment Multimodal Data to Predict Sentinel Lymph Node Status After Neoadjuvant Chemotherapy in Operable Early-stage Breast Cancer.

RATIONALE AND OBJECTIVES: Although accurate preoperative prediction of sentinel lymph node (SLN) status in operable early-stage breast cancer (EBC) af...

Multimodal Deep Fusion of Ultrasound Images and Clinical Factors for Pre-operative Prediction of Lateral Cervical Lymph Node Metastasis in Papillary Thyroid Carcinoma.

OBJECTIVE: Lateral cervical lymph node metastasis (LLNM) is missed in up to 30% of papillary thyroid carcinoma (PTC) patients pre-operatively, leading...