Risk Management

Emergence of associative learning in a neuromorphic inference network.

. In the theoretical framework of predictive coding and active inference, the brain can be viewed as instantiating a rich generative model of the world that predicts incoming sensory data while continuously updating its parameters via minimization of prediction errors. While this theory has been successfully applied to cognitive processes-by modelling the activity of functional neural networks at ...

Sample Size Calculation for Clinical Trials of Medical Decision Support Systems with Binary Outcome.

Currently, software products for use in medicine are actively developed. Among them, the dominant share belongs to clinical decision support systems (CDSS), which can be intelligent (based on mathematical models obtained by machine learning methods or other artificial intelligence technologies) or non-intelligent. For the state registration of CDSSs as software medical products, clinical trials ar...

Systematic review of current natural language processing methods and applications in cardiology.

Natural language processing (NLP) is a set of automated methods to organise and evaluate the information contained in unstructured clinical notes, whi...

Application of Artificial Intelligence Combined with 5G Technology in the Reform of English Teaching in Universities.

The language assistance and learning sectors have currently undergone restructuring in the period of fifth-generation (5G) communication and artificia...

IDL-PPBopt: A Strategy for Prediction and Optimization of Human Plasma Protein Binding of Compounds via an Interpretable Deep Learning Method.

The prediction and optimization of pharmacokinetic properties are essential in lead optimization. Traditional strategies mainly depend on the empirica...

Expedite Quantification of Landslides Using Wireless Sensors and Artificial Intelligence for Data Controlling Practices.

The power of wireless network sensor technologies has enabled the development of large-scale in-house monitoring systems. The sensor may play a big pa...

Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI.

A growing number of artificial intelligence (AI)-based clinical decision support systems are showing promising performance in preclinical, in silico, ...

Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI.

A growing number of artificial intelligence (AI)-based clinical decision support systems are showing promising performance in preclinical, in silico e...

Assessing the potentiality of algorithms and artificial intelligence adoption to disrupt patient primary care with a safer and faster medication management: a systematic review protocol.

INTRODUCTION: In primary care, almost 75% of outpatient visits by family doctors and general practitioners involve continuation or initiation of drug ...

[The role of bile acid measurement in the management of intrahepatic cholestasis of pregnancy].

Introduction: Intrahepatic cholestasis of pregnancy complicates 1% of pregnancies. It increases the risk of severe fetal complications significantly, ...

Formation Control of Automated Guided Vehicles in the Presence of Packet Loss.

This paper presents the formation tracking problem for non-holonomic automated guided vehicles. Specifically, we focus on a decentralized leader-follo...

Safety and feasibility study of non-invasive robot-assisted high-intensity focused ultrasound therapy for the treatment of atherosclerotic plaques in the femoral artery: protocol for a pilot study.

INTRODUCTION: Peripheral arterial disease (PAD) is an atherosclerotic disease leading to stenosis and/or occlusion of the arterial circulation of the ...

Explainable AI in Diagnosing and Anticipating Leukemia Using Transfer Learning Method.

White blood cells (WBCs) are blood cells that fight infections and diseases as a part of the immune system. They are also known as "defender cells." B...

Very low-volume interval training improves nonalcoholic fatty liver disease fibrosis score and cardiometabolic health in adults with obesity and metabolic syndrome.

Non-alcoholic fatty liver disease (NAFLD) and cardiometabolic disorders are highly prevalent in obese individuals. Physical exercise is an important e...

Gradient tree boosting and network propagation for the identification of pan-cancer survival networks.

Cancer survival prediction is typically done with uninterpretable machine learning techniques, e.g., gradient tree boosting. Therefore, additional ste...

Effectiveness and safety of blonanserin for improving social and cognitive functions in patients with first-episode schizophrenia: a study protocol for a prospective, multicentre, single-arm clinical trial.

INTRODUCTION: Both the pharmacological characteristics of blonanserin and its related small sample size studies suggest that blonanserin could allevia...

Smart Healthcare System with Light-Weighted Blockchain System and Deep Learning Techniques.

A radio communication sensor system is a collection of sensor modules that are connected to one another through wireless communication. It is common f...

Effect of an artificial intelligence-assisted tool on non-valvular atrial fibrillation anticoagulation management in primary care: protocol for a cluster randomized controlled trial.

BACKGROUND: Atrial fibrillation (AF) is one of the most common cardiac arrhythmia diseases. Thromboembolic prophylaxis plays an essential role in AF t...

Psychosocial Factors and Psychological Characteristics of Personality of Patients with Chronic Diseases Using Artificial Intelligence Data Mining Technology and Wireless Network Cloud Service Platform.

It was to explore the application value of health cloud service platform based on data mining algorithm and wireless network in the analysis of psycho...

Feasibility of an accelerated 2D-multi-contrast knee MRI protocol using deep-learning image reconstruction: a prospective intraindividual comparison with a standard MRI protocol.

OBJECTIVES: The aim of this study was to evaluate the image quality and diagnostic performance of a deep-learning (DL)-accelerated two-dimensional (2D...