INTRODUCTION: Letters of recommendation (LORs) are a highly influential yet subjective and often enigmatic aspect of the residency application process. This study hypothesizes that LORs do contain valuable insights into applicants and can be used to ...
This study aimed to compare the impact of the partially flipped physiology classroom (PFC) and the traditional lecture-based classroom (TLC) on students' learning approaches. The study was conducted over 5 mo at Xiangya School of Medicine from Februa...
AIM: To develop and employ machine learning (ML) algorithms to analyse electrocardiograms (ECGs) for the diagnosis of cardiac autonomic neuropathy (CAN).
BACKGROUND/AIMS: The performance of machine learning (ML) in predicting the outcomes of patients with hepatocellular carcinoma (HCC) remains uncertain. We aimed to develop risk scores using conventional methods and ML to categorize early-stage HCC pa...
Shapley values from cooperative game theory are adapted for explaining machine learning predictions. For large feature sets used in machine learning, Shapley values are approximated. We present a protocol for two techniques for explaining support vec...
OBJECTIVES: This study aims to explore and discuss recent advancements in tooth reconstruction utilizing deep learning (DL) techniques. A review on new DL methodologies in partial and full tooth reconstruction is conducted.
The purpose of this study was to construct deep learning models for more efficient and reliable sex estimation. Two deep learning models, VGG16 and DenseNet-121, were used in this retrospective study. In total, 600 lateral cephalograms were analyzed....
BACKGROUND: There is mounting evidence that asthma might exacerbate depression. We sought to examine candidates for diagnostic genes in patients suffering from asthma and depression.
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