AIMC Topic: Middle Aged

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Concordance rate of radiologists and a commercialized deep-learning solution for chest X-ray: Real-world experience with a multicenter health screening cohort.

PloS one
PURPOSE: Lunit INSIGHT CXR (Lunit) is a commercially available deep-learning algorithm-based decision support system for chest radiography (CXR). This retrospective study aimed to evaluate the concordance rate of radiologists and Lunit for thoracic a...

Artificial intelligence system for identification of false-negative interpretations in chest radiographs.

European radiology
OBJECTIVES: To investigate the efficacy of an artificial intelligence (AI) system for the identification of false negatives in chest radiographs that were interpreted as normal by radiologists.

Retzius-sparing technique independently predicts early recovery of urinary continence after robot-assisted radical prostatectomy.

Journal of robotic surgery
Robot-assisted radical prostatectomy (RARP) is the conventional surgical treatment option for localised prostate cancer. We investigated factors which may be associated with recovery of early urinary continence (EUC), including the use of the Retzius...

Deep learning identifies Acute Promyelocytic Leukemia in bone marrow smears.

BMC cancer
BACKGROUND: Acute promyelocytic leukemia (APL) is considered a hematologic emergency due to high risk of bleeding and fatal hemorrhages being a major cause of death. Despite lower death rates reported from clinical trials, patient registry data sugge...

Evolution of hospitalized patient characteristics through the first three COVID-19 waves in Paris area using machine learning analysis.

PloS one
Characteristics of patients at risk of developing severe forms of COVID-19 disease have been widely described, but very few studies describe their evolution through the following waves. Data was collected retrospectively from a prospectively maintain...

Artificial intelligence outperforms standard blood-based scores in identifying liver fibrosis patients in primary care.

Scientific reports
For years, hepatologists have been seeking non-invasive methods able to detect significant liver fibrosis. However, no previous algorithm using routine blood markers has proven to be clinically appropriate in primary care. We present a novel approach...