Oncology/Hematology

Blinded, bias-controlled multi-rater evaluation of human-versus-AI brain metastasis segmentation using a hybrid foundation-model framework.

BACKGROUND: Accurate segmentation of brain metastases (BM) is essential for diagnosis, stereotactic radiosurgery planning, and longitudinal assessment. However, manual contouring is time-intensive, limiting clinical scalability, and exhibits substantial inter-observer variability. This variability complicates objective assessment of automated segmentation methods and challenges interpretation of m...

The Big Data Science Center at the Shanghai Synchrotron Radiation Facility: the architecture of the superfacility.

In the context of the global big data deluge, concerted efforts are being made to address the challenges faced by large scientific facilities. These efforts are focused on providing users with the full potential offered by real-time, remote and self-driving experiments, where AI-driven analysis can guide experimental decisions in real time, while ensuring that the data pipelines adhere to the find...

Uncertainty quantification of U-Net based segmentation tool using conformal prediction.

BACKGROUND: The radiation therapy treatment process is very labour intensive, and artificial intelligence (AI) based auto contouring tools are increas...

Deep Unsupervised Domain Adaptation for Translating Cancer Dependency Maps From Cell Lines to Breast Cancer Tumor Genomics.

The Cancer dependency maps (DepMap) identify genetic dependencies in cancer cells using large-scale loss-of-function screens, providing a foundation f...

A Fully Automated Pipeline for Vertebral Structural Assessment From Medical Images. Application Under Metastatic Conditions.

Spinal bone metastases often lead to vertebral fractures and other skeletal events that severely affect patients' quality of life. Predicting structur...

AI-assisted Radiomic Model for Cervical Cancer Recurrence Prediction: A Multicenter Retrospective Study with Experimental Validation.

Purpose To evaluate the value of a nomogram model incorporating clinical parameters, hematologic inflammatory biomarkers, and MRI radiomic features in...

Real-time intraoperative identification of malignant ovarian tumors using deep learning of clinical gross specimen images.

OBJECTIVE: Ovarian cancer is one of the most common gynecologic malignancies with high mortalities. A proper operation strategy is key to improve pati...

Accurate focal-plane selection is crucial for artificial intelligence assessment of three-dimensional urine cytology specimens for bladder cancer screening and surveillance.

BACKGROUND: Bladder cancer is a common and highly recurrent malignancy requiring lifelong surveillance. Urine cytology serves as a noninvasive triage ...

A Narrative Review of Artificial Intelligence for Drug Repurposing: Lessons From COVID-19 and Oncology (2020-2025).

Drug repurposing presents a cost-effective and time-efficient strategy to identify new therapeutic applications for existing drugs. Recent advances in...

The IGF1-PGM5 Axis Inhibits Aerobic Glycolysis and Serves As a Tumor Suppressor in Nasopharyngeal Carcinoma.

Nasopharyngeal carcinoma (NPC) is a prevalent malignancy with a distinct geographical distribution. This study aimed to identify core glycolysis-relat...

Gamma Knife treatment planning using knowledge-based reinforcement learning.

BACKGROUND: Inverse planning is often used for Gamma Knife radiosurgery, allowing clinicians to mathematically specify desired clinical objectives and...

Deep learning in tumour genomics: from multi-omics integration to precision oncology.

Cancer remains a leading cause of death globally, with nearly 10 million deaths in 2020. Advances in genomic technologies have revolutionized cancer r...

Advances and prospects in cell therapy for cancer: explorations from T cells to stem cells.

The increasing global burden of cancer necessitates innovative therapeutic strategies. Cell therapy represents a major breakthrough in oncology, evolv...

Metabolic reprogramming of myeloid cells in cancer: from lactate-NAMPT axis to AI-guided therapeutics.

Myeloid cells-including macrophages, monocytes, neutrophils and dendritic cells-are metabolically plastic sentinels that shape the tumor microenvironm...

Multimodal artificial intelligence models for liver fibrosis staging: a scoping review.

Multimodal artificial intelligence (AI) approaches integrating heterogeneous data sources represent an emerging frontier in liver fibrosis assessment....

An AI-Driven Multi-Omics Framework Identifies CASP8 as a Clinically Actionable Pyroptosis Biomarker in Bladder Cancer.

Despite rapid advances in multi-omics technologies, translating candidate biomarkers into clinical practice for bladder cancer remains challenging due...

Optimized Prostate Cancer Stage Classification Using XGBoost Based on Racial miRNA Expression.

BACKGROUND/AIM: Prostate cancer has a high mortality rate and shows diagnostic disparities between racial groups, particularly between White and Black...

Artificial intelligence-based automated sleep staging using heart rate variability: Assessment of performance and clinical prospects.

Background Some artificial intelligence models use heart rate variability (HRV) features to classify sleep stages. Estimation of HRV indices requires ...

Integrative Genomic and Clinical Profiling of Colorectal Cancer Liver Metastases to Guide Personalized Surgery and Liver Transplantation.

BACKGROUND/AIM: Colorectal cancer liver metastases (CRLM) remain a leading cause of cancer-related mortality. Although hepatic resection is the only e...

Machine Learning-based Prediction of Unplanned Acute Care in Outpatients Receiving S-1 Chemotherapy.

BACKGROUND/AIM: The increasing use of oral anticancer agents in outpatient settings has led to a growing need for unplanned acute care (UAC) due to tr...