General practitioners (GPs) are playing a key role in skin cancer screening. Non-melanoma skin cancer is frequent and difficult to diagnose. We aimed to assess whether GPs are facing difficulties in diagnosing non-pigmented skin tumours (NPSTs) and w...
Automated analysis and quantification of physiological signals in clinical practice and medical research can reduce manual labor, increase efficiency, and provide more objective, reproducible results. To build a novel platform for the analysis of mus...
AIMS: This study used an artificial neural network (ANN) model to determine the most important pre- and perioperative variables to predict same-day discharge in patients undergoing total knee arthroplasty (TKA).
BACKGROUND/AIM: We aimed to investigate the role of radiogenomic and deep learning approaches in predicting the KRAS mutation status of a tumor using radiotherapy planning computed tomography (CT) images in patients with locally advanced rectal cance...
OBJECTIVE: Wound infection is prevalent in home healthcare (HHC) and often leads to hospitalizations. However, none of the previous studies of wounds in HHC have used data from clinical notes. Therefore, the authors created a more accurate descriptio...
PURPOSE: We aimed to evaluate the performance of a deep learning system for differential diagnosis of lung cancer with conventional CT and FDG PET/CT using transfer learning (TL) and metadata.
OBJECTIVE: This study proposes an automated classification of benign and malignant in highly integrated regions in bone single-photon emission computed tomography/computed tomography (SPECT/CT) using a three-dimensional deep convolutional neural netw...
OBJECTIVES: The National Early Warning Score, Modified Early Warning Score, and quick Sepsis-related Organ Failure Assessment can predict clinical deterioration. These scores exhibit only moderate performance and are often evaluated using aggregated ...
PURPOSE: To investigate the effect of denoise processing by artificial intelligence (AI) on the optical coherence tomography angiography (OCTA) images in eyes with retinal lesions.
Accurate and individualized prediction of response to therapies is central to precision medicine. However, because of the generally complex and multifaceted nature of clinical drug response, realizing this vision is highly challenging, requiring inte...
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