Oncology/Hematology

Integrated analysis of oral rinse-derived and plasma circulating tumour DNA for mutation profiling and outcome prediction with oral squamous cell carcinoma.

This study evaluates the potential of oral rinse-derived and plasma circulating tumour DNA (ctDNA) in HPV-negative oral squamous cell carcinoma (OSCC), where early recurrence occurs in a significant proportion of patients, contributing to poor prognosis. Analysis of paired tissue, oral rinse, and plasma samples from 123 patients revealed ctDNA detection rates of 94.3% in oral rinse and 80.5% in pl...

Development of a circadian-related prognostic signature highlights RBM17 as a stemness regulator in liver cancer.

The liver exhibits extensive circadian regulation among organs. Epidemiological studies have substantiated that disruptions in circadian rhythm constitute a risk factor for the oncogenesis of liver cancer. Nonetheless, the molecular underpinnings of how circadian dysregulation influences liver cancer progression remain elusive. Our research aims to elucidate these mechanisms and develop a predicti...

Integration of machine learning in biomarker discovery for esophageal squamous cell carcinoma: Applications and future directions.

PURPOSE: Recent advancements in sequencing technologies and bioinformatics algorithms have facilitated significant breakthroughs in both fundamental a...

A Pipeline for the Automatic Identification of Randomized Controlled Oncology Trials and Assignment of Tumor Entities Using Natural Language Processing.

BACKGROUND: Most tools trying to automatically extract information from medical publications are domain agnostic and process publications from any fie...

The Diagnostic Value of Artificial Intelligence in Oral Squamous Cell Carcinoma: A Systematic Review and Meta-Analysis.

OBJECTIVE: To evaluate the diagnostic performance of artificial intelligence (AI) in detecting oral squamous cell carcinoma (OSCC) through a systemati...

Classifying Stereotactic Radiosurgery Patients by Primary Diagnosis Using Natural Language Processing of Clinical Notes.

PURPOSE: Accurate identification of the primary tumor diagnosis of patients who have undergone stereotactic radiosurgery (SRS) from electronic health ...

Integrating Machine Learning Algorithms to Construct a Triaptosis-Related Prognostic Model in Melanoma.

INTRODUCTION: Melanoma is a highly aggressive skin cancer that accounts for a disproportionate number of skin cancer-related deaths due to early metas...

Development and validation of an MRI spatiotemporal interaction model for early noninvasive prediction of neoadjuvant chemotherapy response in breast cancer: a multicentre study.

BACKGROUND: The accurate and early evaluation of response to neoadjuvant chemotherapy (NAC) in breast cancer is crucial for optimizing treatment strat...

Antifouling Capture and Dual-Targeting Recognition-Induced Signal Amplification for Triple-Mode Detection and Identification of Circulating Tumor Cells.

Circulating tumor cells (CTCs) are promising biomarkers for cancer diagnosis, while detecting CTCs in clinical samples is still challenging due to the...

Noise-Consistent Hypergraph Autoencoder Based on Contrastive Learning for Cancer ceRNA Association Prediction in Complex Biological Regulatory Networks.

Competitive endogenous RNA (ceRNA) regulatory networks (CENA) have advanced our understanding of noncoding RNAs' roles in complex diseases, providing ...

Radiogenomic correlation of hypoxia-related biomarkers in clear cell renal cell carcinoma.

PURPOSE: This study aimed to evaluate radiomic models' ability to predict hypoxia-related biomarker expression in clear cell renal cell carcinoma (ccR...

High visceral-to-subcutaneous fat area ratio is an unfavorable prognostic indicator in patients with uterine sarcoma.

PURPOSE: Uterine sarcoma is a rare disease whose association with body composition parameters is poorly understood. This study explored the impact of ...

Artificial intelligence-based quantitative bone marrow pathology analysis for myeloproliferative neoplasms.

The evaluation of bone marrow pathology is essential for diagnosing and classifying myeloproliferative neoplasms (MPNs). However, morphological assess...

Development of Machine Learning Models to Predict Tumor Endoprosthesis Survival.

BACKGROUND AND OBJECTIVES: Endoprosthetic reconstruction is the preferred approach for limb salvage surgery for many patients following malignant bone...

Simulation-free workflow for lattice radiation therapy using deep learning predicted synthetic computed tomography: A feasibility study.

PURPOSE: Lattice radiation therapy (LRT) is a form of spatially fractionated radiation therapy that allows increased total dose delivery aiming for im...

Integrating transcriptomics and hybrid machine learning enables high-accuracy diagnostic modeling for nasopharyngeal carcinoma.

BACKGROUND: Nasopharyngeal carcinoma (NPC) lacks biomarkers demonstrating both high specificity and sensitivity for early diagnosis. This study aimed ...

Emerging Trends in Artificial Intelligence in Neuro-Oncology.

PURPOSE OF REVIEW: This article explores the evolving role of artificial intelligence (AI) in neuro-oncology, highlighting its potential to enhance di...

OneTouch Automated Photoacoustic and Ultrasound Imaging of Breast in Standing Pose.

We developed an automated photoacoustic and ultrasound breast tomography system that images the patient in the standing pose. The system, named OneTou...

Clinical decision tree for optimising endoscopic assessment of signet ring cell carcinoma in hereditary diffuse gastric cancer surveillance.

Background and study aims Prophylactic total gastrectomy (PTG) is the definitive treatment for hereditary diffuse gastric cancer syndrome (HDGC). Endo...

Preirradiation of Spheroids with Ac-Trastuzumab Improves Penetration of Ac-Liposomes and MIRDcell Predictions of Responses to Drug Cocktails.

This investigation examined the factors involved in predicting the responses of micrometastases to targeted Ac-based therapies and in optimizing these...