AIMC Topic: Clinical Decision-Making

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Right population, right resources, right algorithm: Using machine learning efficiently and effectively in surgical systems where data are a limited resource.

Surgery
There is a growing interest in using machine learning algorithms to support surgical care, diagnostics, and public health surveillance in low- and middle-income countries. From our own experience and the literature, we share several lessons for devel...

Outcomes of surgical and/or medical treatment in patients with prolactinomas during long-term follow-up: a retrospective single-centre study.

Hormone molecular biology and clinical investigation
OBJECTIVES: Prolactinoma is the most common cause of pituitary tumours. Current medical guidelines recommend dopamine agonists (cabergoline or bromocriptine) as the initial therapy for prolactinoma. However, surgical removal can also be considered in...

Multimodal fusion with deep neural networks for leveraging CT imaging and electronic health record: a case-study in pulmonary embolism detection.

Scientific reports
Recent advancements in deep learning have led to a resurgence of medical imaging and Electronic Medical Record (EMR) models for a variety of applications, including clinical decision support, automated workflow triage, clinical prediction and more. H...

One of the first validations of an artificial intelligence algorithm for clinical use: The impact on intraoperative hypotension prediction and clinical decision-making.

Surgery
This review describes the steps and conclusions from the development and validation of an artificial intelligence algorithm (the Hypotension Prediction Index), one of the first machine learning predictive algorithms used in the operating room environ...

Milestones for autonomous in vivo microrobots in medical applications.

Surgery
In light of recent developments within both health care and robotics, the use of robots within the human body has become attainable. Here we discuss the milestones for the realization of autonomous microrobots in medical applications. The desired tas...

Clinically applicable approach for predicting mechanical ventilation in patients with COVID-19.

British journal of anaesthesia
BACKGROUND: Patients with coronavirus disease 2019 (COVID-19) requiring mechanical ventilation have high mortality and resource utilisation. The ability to predict which patients may require mechanical ventilation allows increased acuity of care and ...

Machine learning to predict mortality after rehabilitation among patients with severe stroke.

Scientific reports
Stroke is among the leading causes of death and disability worldwide. Approximately 20-25% of stroke survivors present severe disability, which is associated with increased mortality risk. Prognostication is inherent in the process of clinical decisi...