Latest AI and machine learning research in oncology/hematology for healthcare professionals.
In the mid-twentieth century, the social movement of death revivalism sought to resist the medicalis...
OBJECTIVES: This study combined two novel approaches in oncology patient outcome predictions-body co...
Rehabilitation is a major requirement to improve the quality of life and mobility of patients with d...
The Adenosine A receptor (AAR) is considered a novel potential target for the immunotherapy of cance...
INTRODUCTION: Despite several therapeutic efforts, lung cancer remains a highly lethal disease. Nove...
Low-cost optical imaging technologies have the potential to reduce inequalities in healthcare by imp...
PURPOSE: This paper presents a deep learning model for use in the automated segmentation of metastat...
BACKGROUND: Kidney renal clear cell carcinoma (KIRC), as a common case in renal cell carcinoma (RCC)...
BACKGROUND: Up to 15.3% of papillary thyroid microcarcinoma (PTMC) patients with negative clinical l...
Background Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer (PC)...
OBJECTIVES: This study aimed to explore the value of an artificial intelligence (AI)-assisted diagno...
This study introduces a sophisticated computational pipeline, , designed for the discovery of antiv...
BACKGROUND: Achieving endoscopic and histological remission is a critical treatment objective in ulc...
The cellular immune response comprises several processes, with the most notable ones being the bindi...
BACKGROUND: The rising global cancer burden has led to an increasing demand for imaging tests such a...
BACKGROUND: Magnetic resonance image only (MRI-only) simulation for head and neck (H&N) radiotherapy...
The use of non-invasive tools in conjunction with artificial intelligence (AI) to detect diseases ha...
Thyroid cancer, a prevalent form of endocrine malignancy, has witnessed a substantial increase in oc...
Children, adolescents, and young adult cancer survivors (CAYAs) constitute a growing population requ...
OBJECTIVE: Deep learning (DL) has shown promising results for improving mammographic breast cancer d...
OBJECTIVES: To establish deep learning models for malignancy risk estimation of sub-centimeter pulmo...