Latest AI and machine learning research in other cancers for healthcare professionals.
OBJECTIVE: The incidence of non-melanoma skin cancers, encompassing basal cell carcinoma (BCC) and c...
Boron neutron capture therapy (BNCT) is a highly targeted, selective and effective technique to cure...
Brain tumors pose significant global health concerns due to their high mortality rates and limited t...
BACKGROUND: The integration of artificial intelligence (AI), particularly, in oncology, has signific...
Sleep staging plays a critical role in evaluating the quality of sleep. Currently, most studies are ...
AIMS: This study aims to use deep learning (DL) to classify thyroid nodules as benign and malignant ...
PURPOSE: Mucinous breast carcinoma (MBC) tends to be misdiagnosed as fibroadenomas (FA) due to its b...
In breast carcinoma, invasive ductal carcinoma (IDC) is the most common histopathologic subtype, and...
To meet the needs of automated medical analysis of brain tumor magnetic resonance imaging, this stud...
The effectiveness of ultrasonography (USG) in liver cancer screening is partly constrained by the op...
Identifying the progression stages of Alzheimer's disease (AD) can be considered as an imbalanced mu...
BACKGROUND AND AIMS: Colorectal cancer (CRC) is the third most prevalent cancer globally, posing a s...
BACKGROUND AND OBJECTIVE: Automatic sleep staging is essential for assessing and diagnosing sleep di...
In digital pathology, accurate mitosis detection in histopathological images is critical for cancer ...
OBJECTIVE: To predict preoperative inguinal lymph node metastasis in vulvar cancer patients using a ...
BACKGROUND: Axillary lymph node dissection (ALND) is a standard procedure for early-stage breast can...
BACKGROUND: In oncology, electronic health records contain textual key information for the diagnosis...
BACKGROUND: The accuracy of traditional clinical methods for assessing the metastatic status of axil...
Various forms of programmed cell death (PCD) collectively regulate the occurrence, development and m...
OBJECTIVES: This study aimed to utilize MR radiomics-based machine learning classifiers on a large-s...
STUDY DESIGN: This is a retrospective cohort study utilizing machine learning to predict postoperati...