Latest AI and machine learning research in oncology/hematology for healthcare professionals.
To assess whether application of a support vector machine learning algorithm to ancillary data obtained from posterior-anterior dual-energy X-ray absorptiometry (DEXA) studies could identify patients with lumbar spine (L1-L4) vertebral body fractures without additional DEXA imaging or radiation. Three hundred seven patients (199 without any fractures of the spine, and 108 patients with at least on...
BACKGROUND: A preoperative estimation of survival is critical for deciding on the operative management of metastatic bone disease of the extremities. Several tools have been developed for this purpose, but there is room for improvement. Machine learning is an increasingly popular and flexible method of prediction model building based on a data set. It raises some skepticism, however, because of th...
Drug sensitivity prediction is one of the critical tasks involved in drug designing and discovery. Recently several online databases and consortiums h...
BACKGROUND: Localized renal cell carcinoma is increasingly relevant in daily urological practice due to earlier diagnosis and higher life expectancy.
INTRODUCTION: Thoracic diseases include a variety of common human primary malignant tumors, among which lung cancer and esophageal cancer are among th...
INTRODUCTION: Peritoneal metastasis (PM) is a frequent condition in patients presenting with gastric cancer, especially in younger patients with advan...
Machine learning-based early warning systems (EWSs) can detect clinical deterioration more accurately than point-score tools. In patients with sepsis,...
By changing the lifestyle and increasing the cancer incidence, accurate diagnosis becomes a significant medical action. Today, DNA microarray is widel...
AIM AND OBJECTIVE: Leukemia is the second common blood cancer after lymphoma, and its incidence rate has an increasing trend in recent years. Leukemia...
IMPORTANCE: Thyroid nodules are common incidental findings. Ultrasonography and molecular testing can be used to assess risk of malignant neoplasm.
BACKGROUND: Molecular profiling has become essential for tumor risk stratification and treatment selection. However, cancer genome complexity and tech...
IMPORTANCE: Diagnosing the site of origin for cancer is a pillar of disease classification that has directed clinical care for more than a century. Ev...
The integration of multi-modal data, such as histopathological images and genomic data, is essential for understanding cancer heterogeneity and comple...
BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) is the seventh most common type of cancer around the world. The aim of this study was to see...
RATIONALE AND OBJECTIVES: Our primary aim was to improve radiology reports by increasing concordance of target lesion measurements with oncology recor...
BACKGROUND: Lung cancer has become a major cause of cancer-related deaths. Detection of potentially malignant lung nodules is essential for the early ...
This chapter proposes a method to detect metastatic liver cancer from X-ray CT images using a convolutional neural network (CNN). The proposed method ...
High-throughput and streamlined workflows are essential in clinical proteomics for standardized processing of samples from a variety of sources, inclu...
BACKGROUND AND AIM: Although the prognosis of nasopharyngeal cancer largely depends on a classification based on the tumor-lymph node metastasis stagi...
BACKGROUND: The diagnosis and prognosis of pathological conditions, such as age-related macular degeneration (AMD) and cancer still need improvement. ...