Other Cancers

In the artificial intelligence age, is Oswestry spinal risk index still useful? an external validation of Oswestry spinal risk index applied to radiotherapy patients and its relevance.

BACKGROUND AND STUDY AIMS: In 2013, Balain et al. proposed a scoring system, the Oswestry Spinal Ris...

Advances and applications in tumor organoid research Harnessing human tumor organoids for cancer modeling and precision therapy.

Human tumor organoids represent a paradigm shift in cancer modeling, overcoming critical limitations...

Kaposi's sarcoma in individuals living with HIV: comparative assessment of AI-based clinical responses using a standardized questionnaire set.

OBJECTIVE: To comparatively evaluate the clinical responses of three digital platforms (ChatGPT 5.2,...

Pioneering efficient deep learning architectures for enhanced hepatocellular carcinoma prediction and clinical translation.

BACKGROUND: Hepatocellular carcinoma (HCC) is a major cause of cancer-related mortality worldwide an...

Dental Students' Knowledge, Attitudes and Perceptions of Artificial Intelligence Tools to Aid in the Diagnosis of Oral Cancer and Oral Potentially Malignant Disorders.

BACKGROUND: Artificial intelligence (AI) has emerged as a promising tool in dentistry, particularly ...

Evolving strategies in prostate cancer: Emerging approaches and unmet needs from the Bridging the Gaps in Prostate Cancer expert panel.

BACKGROUND: The expansion of treatment options for prostate cancer (PC) has improved disease-specifi...

Multimodal hybrid mamba classification model for tumor pathological grade prediction using magnetic resonance images.

Malignant tumors present a significant global health challenge, and accurate pathological grading is...

The emerging role of machine learning-based methods in cancer classification using microRNA.

Early detection and accurate classification of cancer are crucial to improving patient outcomes. Dia...

Integrative bioinformatics identifies NSCLC biomarkers associated with LPS metabolism and circadian disruption.

PURPOSE: Non-small cell lung carcinoma (NSCLC) is a leading cause of cancer-related mortality worldw...

Deep learning for histopathological diagnosis of esophageal squamous cell carcinoma in biopsies: A multicenter analysis.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a major cause of cancer mortality in Asia, ...

Kinic index: an artificial intelligence-driven predictive model and multitarget drug discovery framework for hepatocellular carcinoma patients.

Hepatocellular carcinoma (HCC) remains a major global health challenge due to its molecular heteroge...

Association of cardiovascular-kidney-metabolic syndrome stages with MASLD prevalence and liver fibrosis severity: evidence from traditional and machine learning approaches.

INTRODUCTION: Cardiovascular-Kidney-Metabolic (CKM) syndrome reflects the convergence of cardiovascu...

CT-based multiple instance and ensemble learning for lymph node metastasis prediction in esophageal squamous cell carcinoma: a multicentre, retrospective study.

Predicting neoadjuvant immunotherapy efficacy with machine learning models in non-small cell lung cancer: A systematic review and meta analysis.

BACKGROUND: The response of resectable non-small cell lung cancer (NSCLC) to neoadjuvant immunothera...

Development of a Predictive Calculator for the Need for Abdominoperineal Resection after Chemoradiation Therapy in Anal Squamous Cell Carcinoma.

BACKGROUND: Chemoradiation therapy (CRT) is standard treatment for anal squamous cell carcinoma (ASC...

Automating classification of treatment responses to combined targeted therapy and immunotherapy in HCC.

Tyrosine kinase inhibitor (TKI) combined with immunotherapy regimens are now widely used for treatin...

Radiomics analysis of MRI improves prediction of lymph node metastasis in laryngeal squamous cell carcinoma.

OBJECTIVE: To explore the role of multi-sequence magnetic resonance imaging (MRI) images in preopera...

Potential mechanisms of Si-Wu-Tang against esophageal squamous cell carcinoma: A machine learning pharmacological study.

The purpose of this study is to explore the potential mechanism of Si-Wu-Tang (SWT) against esophage...

Generative artificial intelligence for patient education material on gastric cancer prevention.

BACKGROUND:  This study assessed the effectiveness of large language models (LLMs) in generating lay...

Interpreting cancer genetics through a two-step "evolutionary cascade hypothesis": bridging neutral and selective perspectives.

BACKGROUND: DNA mutations are the fundamental engines of cancer, driving its initiation and progress...

Interpretable machine learning based on intratumoral and peritumoral ultrasound radiomics for predicting central lymph node metastasis in papillary thyroid carcinoma.

OBJECTIVES: This retrospective and single-center study aimed to develop machine learning (ML) model ...