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Predicting short- and long-term glycated haemoglobin response after insulin initiation in patients with type 2 diabetes mellitus using machine-learning algorithms.

Diabetes, obesity & metabolism
AIM: To assess the potential of supervised machine-learning techniques to identify clinical variables for predicting short-term and long-term glycated haemoglobin (HbA1c) response after insulin treatment initiation in patients with type 2 diabetes me...

Endocan serum concentration in uninfected newborn infants.

Journal of infection in developing countries
INTRODUCTION: Endocan is a specific endothelial mediator involved in the inflammatory response. Its role in the diagnosis of sepsis has been studied in adult patients and late onset neonatal sepsis. The clinical signs of early onset sepsis (EOS) are ...

Robotic anatomic pulmonary segmentectomy: technical approach and outcomes.

Revista do Colegio Brasileiro de Cirurgioes
OBJECTIVE: to report our initial experience with pulmonary robotic segmentectomy, describing the surgical technique, the preferred positioning of portals, initial results and outcomes.

Validation of an alcohol misuse classifier in hospitalized patients.

Alcohol (Fayetteville, N.Y.)
BACKGROUND: Current modes of identifying alcohol misuse in hospitalized patients rely on self-report questionnaires and diagnostic codes that have limitations, including low sensitivity. Information in the clinical notes of the electronic health reco...

Comparison of CT and MRI images for the prediction of soft-tissue sarcoma grading and lung metastasis via a convolutional neural networks model.

Clinical radiology
AIM: To realise the automated prediction of soft-tissue sarcoma (STS) grading and lung metastasis based on computed tomography (CT), T1-weighted (T1W) magnetic resonance imaging (MRI), and fat-suppressed T2-weighted MRI (FST2W) via the convolutional ...

Improving documentation of presenting problems in the emergency department using a domain-specific ontology and machine learning-driven user interfaces.

International journal of medical informatics
OBJECTIVES: To determine the effect of a domain-specific ontology and machine learning-driven user interfaces on the efficiency and quality of documentation of presenting problems (chief complaints) in the emergency department (ED).

A deep learning framework for automatic diagnosis of unipolar depression.

International journal of medical informatics
BACKGROUND AND PURPOSE: In recent years, the development of machine learning (ML) frameworks for automatic diagnosis of unipolar depression has escalated to a next level of deep learning frameworks. However, this idea needs further validation. Theref...

Multilevel Features for Sensor-Based Assessment of Motor Fluctuation in Parkinson's Disease Subjects.

IEEE journal of biomedical and health informatics
Motor fluctuations are a frequent complication in patients with Parkinson's disease (PD) where the response to medication fluctuates between ON states (medication working) and OFF states (medication has worn off). This paper describes a new data anal...

Development of a clinical support system for identifying social frailty.

International journal of medical informatics
OBJECTIVE: Recognizing frailty, also known as clinical geriatric syndrome in the elderly that is characterized by high vulnerability and low resilience, and its extensive influence in clinical practice is challenging. This study aims to develop a soc...