Malignant salivary gland tumors represent a challenge for pathologists due to their low frequency and morphologic overlap. In recent years machine learning techniques have been applied to the field of pathology to improve diagnostic performance. In t...
OBJECTIVE: To develop a machine learning-based prediction model for incident radiographic osteoarthritis (OA) of the knee over 8 years using MRI-based cartilage biochemical composition and knee joint structure, demographics, and clinical predictors i...
Cardiotoxicity is a severe side effect for colorectal cancer (CRC) patients undergoing fluoropyrimidine-based chemotherapy. To develop and compare machine learning algorithms to predict cardiotoxicity risk among nationally representative CRC patients...
Early theories of efficient coding suggested the visual system could compress the world by learning to represent features where information was concentrated, such as contours. This view was validated by the discovery that neurons in posterior visual ...
BACKGROUND: Robot-assisted laparoscopic prostatectomy (RALP) is a favored surgical approach for treating prostate cancer. However, RALP does not decrease postoperative pain significantly despite its minimal invasiveness. The pain associated with robo...
Multiple types of genomic variations are present in cutaneous melanoma and some of the genomic features may have an impact on the prognosis of the disease. The access to genomics data via public repositories such as The Cancer Genome Atlas (TCGA) all...
Recognizing others' social interactions is a crucial human ability. Using simple stimuli, previous studies have shown that social interactions are selectively processed in the superior temporal sulcus (STS), but prior work with movies has suggested t...
OBJECTIVES: This study was conducted to examine gender differences in under-reporting hiring discrimination by building a prediction model for workers who responded "not applicable (NA)" to a question about hiring discrimination despite being eligibl...
OBJECTIVES: To assess Prostate Imaging Reporting and Data System (PI-RADS)-trained deep learning (DL) algorithm performance and to investigate the effect of data size and prior knowledge on the detection of clinically significant prostate cancer (csP...
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