Oncology/Hematology

CT-based subregional and peritumoral radiomics for predicting pathological T stage of clear cell renal cell carcinoma: an exploratory study of biological mechanisms.

OBJECTIVES: To evaluate intratumoral subregional and peritumoral radiomics for predicting pathological T stage of clear cell renal cell carcinoma (ccRCC), and investigate the biological mechanisms of radiomics. MATERIALS AND METHODS: This retrospective study included 323 ccRCC patients from two centers, divided into training (n = 148), internal test (n = 38), and external validation (n = 137) sets...

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 Risk Index (OSRI), to predict survival in patients with spinal metastases (SM) and hence aid treatment decisions. This study aims to externally validate the OSRI for patients treated exclusively with radiotherapy, and assess its relevance in emergency decision making in the age of nomograms and machine...

Digital pathology-based artificial intelligence algorithms in prostate cancer: inside the 'black box'.

Artificial intelligence (AI) algorithms leveraging digital pathology slides are currently transforming the way urological cancers are diagnosed and gr...

Emerging Roles of Multiparametric Biodosimetry and Artificial Intelligence in Advancing Radiation Dose Assessment for Triage.

Biodosimetry plays a crucial role in radiation emergency preparedness and response by enabling efficient allocation of medical resources through prior...

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 of conventional systems by faithfully recapitulat...

Machine learning-predicted insulin resistance is a risk factor for 12 types of cancer.

Insulin resistance is suggested to be a risk factor for cancer; however, large-scale epidemiological evidence linking insulin resistance to cancer rem...

A Flexible Hybrid Quantum-classical Training Framework of Organ-at-Risk and Tumor Segmentation Models for Radiation Therapy Planning.

Deep learning-based Organ-at-Risk (OAR) and tumor segmentation is vital for radiation therapy planning but often suffers from over-parameterization, r...

Artificial intelligence-based incident analysis and learning system to enhance patient safety and improve treatment quality.

Patient safety and high treatment quality are essential in modern healthcare, but analyzing safety incidents for insights is labor-intensive and incon...

Utilisation of intramuscular and intermuscular fat to develop a new skeletal muscle grading score which can predict treatment outcomes for locally advanced rectal cancer.

BACKGROUND: Sarcopenia has been widely studied in rectal cancer with increasing evidence to suggest that other body composition parameters, in particu...

Breathomics Analysis for Early Diagnosis of Lung Cancer Based on PTR-TOF MS: A Large Sample Size Cross-Sectional Study.

INTRODUCTION: Lung cancer remains a leading cause of cancer mortality globally, emphasising the critical need for non-invasive and cost-effective earl...

Machine Learning-Assisted Screening of High-Entropy Sub-1 nm Nanowires for Ultrasound-Augmented Pancatalytic Tumor Therapy.

The rational design of catalytic nanomaterials, particularly high-entropy alloy (HEA) nanomaterials with their unique structures, is crucial for advan...

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, DeepSeek, Consensus) in terms of responsiveness, ...

The Anti-proliferative and Pro-apoptotic Effects of Iranian Viper Venom (Vipera raddei kurdistanica) on Human Gastric Cancer Cells (C615) are Mediated by PI3K/AKT/mTOR Signalling Pathway Inhibition.

OBJECTIVE: Gastric cancer (GC) is one of the most common malignancies worldwide. Since the PI3K/AKT/mTOR signalling pathway plays a crucial role in tu...

Deep learning in lower gastrointestinal cancer detection: Advances in endoscopic, radiologic, and histopathologic diagnostics.

Gastrointestinal (GI) cancers, particularly colorectal cancer, continue to be a major contributor to global cancer-related morbidity and mortality. De...

Application value of multiphase contrast-enhanced computed tomography radiomics in preoperative evaluation of peritoneal metastasis in gastric cancer.

BACKGROUND: Peritoneal metastasis occurs in 10%-45% of gastric cancer patients and significantly impacts prognosis and treatment decisions. Traditiona...

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 and is often diagnosed at advanced stages, reducing ...

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 in the early detection of oral cancer (OC) and ora...

Toward Timely Diagnosis of Pancreatic Cancer: Revolutionizing Early Detection Through Genomics, Artificial Intelligence, and Noninvasive Biomarkers.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) remains one of the most aggressive cancers, typically diagnosed at an advanced stage due to its su...

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-specific and overall survival outcomes but has also raise...

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 essential for personalized treatment. Traditional...