Latest AI and machine learning research in oncology/hematology for healthcare professionals.
Artificial intelligence (AI) will impact a large proportion of jobs in the short to medium term, especially in the developed countries. The consequences will be felt across many sectors including health care, a critical sector for implementation of AI tools because glitches in algorithms or biases in training datasets may lead to suboptimal treatment that may negatively affect the health of an ind...
Analysing the genome, epigenome, transcriptome, proteome, and metabolome within the spatial context of cells has transformed our understanding of tumour spatiotemporal heterogeneity. Advances in spatial multi-omics technologies now reveal complex molecular interactions shaping cellular behaviour and tissue dynamics. This review highlights key technologies and computational methods that have advanc...
AIM: This case series aimed to explore the occurrence of synchronous hepatocellular carcinoma (HCC) and gastrointestinal adenocarcinoma in cirrhotic p...
BACKGROUND: Microsatellite instability (MSI) has emerged as a predictive biomarker for immunotherapy response in various cancers, but its role in non-...
INTRODUCTION: Bone metastases and pathological fractures significantly impact the prognosis and quality of life in cancer patients. However, clinical ...
This review examines diagnostic methods for prostate cancer, focusing on the role of digital rectal examination (DRE) alongside modern advancements li...
Purpose To evaluate two automated tools for detecting lesions on fluorine 18 (F) fluoroestradiol (FES) PET/CT images and assess concordance of F-FES P...
BACKGROUND AND OBJECTIVES: Accurate survival prediction for pancreatic ductal adenocarcinoma (PDAC) is crucial for personalized treatment strategies. ...
PURPOSE: Although large language models (LLMs) are increasingly used in clinical practice, formal assessments of their quality, accuracy, and effectiv...
BACKGROUND: The Paris System (TPS) introduced standardized nuclear-to-cytoplasmic (N/C) ratio thresholds for urine cytology to improve high-grade urot...
The Mary Tyler Moore Vision Initiative (MTM Vision) honors Mary Tyler Moore's commitment to ending vision loss from diabetes. Founded by Moore's husba...
BackgroundThe primary challenges in PET/MR imaging include prolonged scan durations for both PET and MR components and radiation exposure associated w...
PURPOSE: Artificial intelligence (AI) tools could improve clinical decision making or exacerbate inequities because of bias. African American (AA) men...
Non-muscle-invasive bladder cancer (NMIBC) is a relentless challenge in oncology, with recurrence rates soaring as high as 70-80%. Each recurrence t...
Objective: A number of machine learning models have utilized semantic features, deep features, or both to assess lung nodule malignancy. However, th...
Multi-modal 3D medical image segmentation aims to accurately identify tumor regions across different modalities, facing challenges from variations i...
RATIONALE: Panax quinquefolius L. (PQ), a commonly used traditional Chinese medicine and a food, is usually processed into various products, including...
This study presents a convolutional neural network (CNN)-based approach for the multi-class classification of brain tumors using magnetic resonance ...
This study integrates PET metabolic information with CT anatomical structures to establish a 3D multimodal segmentation dataset for lymphoma based o...
Cervical cancer remains a significant health challenge, with high incidence and mortality rates, particularly in transitioning countries. Convention...