Latest AI and machine learning research in oncology/hematology for healthcare professionals.
OBJECTIVE: Colposcopy involves subjective visual assessment of cervical features that may indicate cervical dysplasia. Pattern recognition during colposcopy could be enhanced by artificial intelligence (AI). Using colposcopy images with precisely mapped multiple biopsy sites and corresponding histologic diagnoses, we developed an AI model, Cervix-AID-Net, to classify colposcopy images into low-gra...
OBJECTIVE: To stratify the risk of bacteremia at the time of emergency department (ED) admission in patients with hematologic malignancies. To this end, we compared the performance of unsupervised and supervised machine learning algorithms with the classical multivariable logistic regression model. METHODS: We conducted a multicenter, international, retrospective cohort study including consecutive...
PURPOSE: To identify independent determinants influencing therapeutic outcomes of initial radioactive iodine (1 3 1I) therapy in differentiated thyroi...
BACKGROUND: Actinic keratosis (AK) is a precancerous skin lesion with the potential to progress into squamous cell carcinoma (SCC), with an overall pr...
BACKGROUND/AIM: Cisplatin resistance remains a major obstacle in advanced gastric cancer (GC). This study aimed to identify key molecular determinants...
BACKGROUND/AIM: The incidence of postoperative complications in minimally-invasive surgery for pancreatic disease remains a concern. The application o...
Osteosarcoma, the most common primary malignant bone tumour, presents significant treatment challenges due to its complex tumour microenvironment and ...
BACKGROUND: Positioning accuracy in radiotherapy is critical for treatment outcomes, especially in head tumor radiotherapy, where the target area is s...
PURPOSE: To develop a deep learning (DL)-based automated segmentation model for rectal cancer on T2-weighted (T2W) magnetic resonance (MR) images. MAT...
PURPOSE: Ambiguous or incomplete documentation is a recurrent bottleneck in radiation oncology workflows, leading to inefficiencies in communication a...
Cardiac arrhythmia is increasingly encountered in patients with cancer, not only as a result of shared risk factors but also as a direct consequence o...
The tissue-level processes underpinning metastatic outgrowth remain unclear. We combined single-cell RNA sequencing, spatial transcriptomics, and AI-s...
Representation learning of Whole slide image (WSI) is fundamental to computational pathology, enabling tasks such as tumor subtyping, survival predict...
Accurate, non-invasive liver fibrosis detection is essential for chronic liver disease management, particularly with rising metabolic dysfunction-asso...
We developed SwiftMHC, an ultra-fast and accurate structure-based framework for peptide-MHC (pMHC) modeling and binding affinity prediction. Using tas...
The construction of concrete structures in high-altitude cold regions faces unique challenges, including intense radiation, low atmospheric pressure, ...
Pediatric neuro-oncology is a critical field of neurosurgery, representing the leading cause of disease-related mortality in children. Despite its rar...
UNLABELLED: Neutropenic fever (NF) is often the first sign of infection in patients with hematologic malignancies, but its cause is frequently unknown...
PURPOSE OF REVIEW: Biochemical recurrence (BCR) after radical prostatectomy occurs in up to one-third of patients and increases the risk of metastasis...
PURPOSE: Sarcopenia has already been widely investigated as a potential indicator of negative outcomes in oncology patients. Our aim was to evaluate t...