To develop an interpretable machine learning (ML) model for predicting surgical outcomes in renal hilar tumors and propose a hilar-specific anatomical nephrometry scoring system. A total of 414 ...
Abstract: The exponential increase in the adoption of Electric Vehicles (EVs) presents significant problems to the stability of the power grid. Therefore, it is crucial to accurately anticipate the ...
The authors attempt to identify which patients with benign lesions will progress to cancer using a liquid biomarker. Although the study is valuable, the evidence provided for the liquid biopsy EV ...
Objectives This study aimed to employ machine learning algorithms to predict the factors contributing to zero-dose children in Tanzania, using the most recent nationally representative data. Design ...
This multicenter retrospective study analyzed patient data from two provinces in China. The derivation cohort included 292 patients treated at The Second Hospital of Nanjing from January 2022 to ...
Abstract: Globally, one of the most fundamental applications of time-series data is stock market forecasting, where each and every second is crucial and analysis is unpredictable, posing a significant ...
Background: The number of patients with cerebral small vessel disease is increasing, especially among the elderly population. With the continuous improvement of detection techniques, the positivity ...
Mr. Ferguson is a documentary filmmaker. As you scroll through the internet, you’ve probably noticed the same problem Kirby Ferguson has: “Everything looks the same, sounds the same, is the same.” In ...
Background: Acute Type A Aortic Dissection (ATAAD) is a lethal disease with limited predictability globally. Cancer, a severe public health issue worldwide, has now become the second leading cause of ...
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