Latest AI and machine learning research in oncology/hematology for healthcare professionals.
Brain tumor resection is a complex procedure with significant implications for patient survival and quality of life. Predictions of patient outcomes provide clinicians and patients the opportunity to select the most suitable onco-functional balance. In this study, global features derived from structural magnetic resonance imaging in a clinical dataset of 49 pre- and post-surgery patients identif...
Colorectal cancer (CRC) is the third most diagnosed cancer and the second leading cause of cancer-related death worldwide. Accurate histopathological grading of CRC is essential for prognosis and treatment planning but remains a subjective process prone to observer variability and limited by global shortages of trained pathologists. To promote automated and standardized solutions, we organized t...
Medical AI diagnosis including histopathology segmentation has derived benefits from the recent development of deep learning technology. However, de...
Cancer is a deadly disease that occurs due to the uncontrolled growth of abnormal cells. Bone cancer is the third most occurring disease; approximatel...
Ovarian tumor, as a common gynecological disease, can rapidly deteriorate into serious health crises when undetected early, thus posing significant ...
Effective communication is essential in cancer care, yet patients often face challenges in preparing for complex medical visits. We present an inter...
Lung cancer is a malignant tumor that poses a serious threat to human health. Existing lung cancer diagnostic techniques face the challenges of high c...
Hematoxylin and Eosin (H&E)-stained images are commonly used to detect nuclear or cancerous regions in cells from images captured by a microscope. I...
The importance of rapid and accurate histologic analysis of surgical tissue in the operating room has been recognized for over a century. Our standa...
Predicting drug responses using genetic and transcriptomic features is crucial for enhancing personalized medicine. In this study, we implemented an...
Magnetic resonance imaging-guided adaptive radiotherapy (MRIgART) is a promising technique for long-course radiotherapy of large-volume brain metastas...
Effective communication in serious illness and palliative care is essential but often under-taught due to limited access to training resources like ...
Low-dose computed tomography (LDCT) imaging employed in lung cancer screening (LCS) programs is increasing in uptake worldwide. LCS programs herald ...
PanTS is a large-scale, multi-institutional dataset curated to advance research in pancreatic CT analysis. It contains 36,390 CT scans from 145 medi...
The use of deep learning (DL) in medical image analysis has significantly improved the ability to predict lung cancer. In this study, we introduce a...
Single-cell sequencing technology has profoundly revolutionized the field of cancer genomics, enabling researchers to explore gene expression profiles...
Neoantigens represent a class of antigens within tumor microenvironments that arise from diverse somatic mutations and aberrations specific to tumorig...
Understanding the vast noncoding cancer genome requires cutting-edge, high-resolution, and accessible strategies. Artificial intelligence is revolutio...
UNLABELLED: Early cancer diagnosis is crucial but challenging owing to the lack of reliable biomarkers that can be measured using routine clinical met...
UNLABELLED: Accurate preoperative assessment of lymph node metastasis (LNM) and overall survival (OS) status is essential for patients with locally ad...