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Nowadays, machine learning (ML) has attained a high level of achievement in many contexts. Considering the significance of ML in medical and bioinformatics owing to its accuracy, many investigators discussed multiple solutions for developing the ...

Combining domain knowledge (DK) and machine learning is a recent research stream to overcome multiple issues like limited explainability, lack of data, and insufficient robustness. Most approaches applying informed machine learning (IML), however,...

• In recent years, ML models are frequently combined with domain knowledge.
• Medical DK is provided by experts, so research should investigate their decisions.
• The motives for MedIML are manifold and guidelines on including DK are ...

The huge amount of data being handled today in any environment, such as energy, economics or healthcare, makes data management systems key to extracting information, analysing and creating more efficient daily processes in these ...

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• We propose a new platform that uses Big Data technologies to manage and apply AI.

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Identifying practice-ready evidence-based journal articles in medicine is a challenge due to the sheer volume of biomedical research publications. Newer approaches to support evidence discovery apply deep learning techniques to improve ...

Ovarian cancer is a significant health issue with lasting impacts on the community. Despite recent advances in surgical, chemotherapeutic and radiotherapeutic interventions, they have had only marginal impacts due to an inability to ...

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• Machine learning and Shapley analysis are suitable for biomarker discovery tasks.
• Pipeline achieves consistent result with statistical analysis on feature contribution.
• Shapley analysis provides opportunities for accountability via ...

Recent progress in artificial intelligence and machine learning has led to the growth of research in every aspect of life including the health care domain. However, privacy risks and legislations hinder the availability of patient data to ...

• A narrative review of the state of the art in synthetic data generation in healthcare.
• We investigate the strengths and weaknesses of existing approaches for synthetic medical data generation.
• We provide consolidation and ...

Health informatics is one of the most developed field in recent time. Computational Intelligence is among the most influential factors that may help to improve patient oriented and secure decision support model. In this article we ...

• Improved data imbalancing model for deep neural networks.
• BiLSTM neural network ...

This review aims to collect, analyse and synthesize the available evidence that can be provided by Wikipedia for epidemiologic surveillance purposes. PRISMA guidelines were followed. PubMed/Medline and Scopus were consulted. Out of 238 ...

• This review shows an increased academic interest in Wikipedia searches and the epidemiology of infectious diseases.

In the medical domain there exists a terminological gap between patients and caregivers and the healthcare professionals. This gap may hinder the success of the communication between healthcare consumers and professionals in the field, with ...

• We propose a method to map lay expressions into the Human Phenotype Ontology.
• Inspired in machine translation we design different deep learning architectures.
• We explore strategies to encode the semantic space of the terms in the ...

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• A comprehensive and in-deep review of studies on health monitoring systems that performed data mining tasks in real-time.

Health monitoring systems (HMSs) capture physiological measurements through biosensors (sensing), obtain significant properties and measures from the output signal (perceiving), use algorithms for data analysis (reasoning), and trigger ...

To date, most HIE studies have investigated user perceptions of value prior to use. Few studies have assessed factors associated with the value of HIE through its actual use. This study investigates provider perceptions on HIE comparing those who ...

• Several methods have been developed to estimate renal risk, however with a high margin of error and difficult to interpret.

With aging, patients with diabetic kidney disease (DKD) show progressive decrease in kidney function. We investigated whether the deviation of biological age (BA) from the chronological age (CA) due ...

In this paper, we provide an overview of the ninth annual edition of the CLEF eHealth evaluation lab. CLEF eHealth 2021 continues our evaluation resource building efforts around the easing and support of patients, their next-of-kins, health care ...

ICD-9-CM Volume 3 (ICD-9-CM-3), as a subset of the ICD-9-CM, is a standard system used to classify operations and medical procedures for billing purposes. With the gradual maturity of the DRG system, the precise coding of ICD-9-CM-3 is ...

Several pathogenic yeast species are resistant to pharmaceutical agents and have evolved so quickly over time that often they cannot be stopped with antifungal treatments. In particular, Candida species can cause yeast infections in patients’ ...

Artificial intelligence (AI) and medical informatics research fields have considerable overlap, with technologies supporting different health issues in different contexts. In this work, we aimed to map out and understand the contributions of AI in ...

Early detection of sepsis can facilitate early clinical intervention with effective treatment and may reduce sepsis mortality rates. In view of this, machine learning-based automated diagnosis of sepsis using easily recordable ...

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• This work applies mutual information tensor analysis on EHR data for sepsis detection.

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• Addresses the use of IoT devices in cancer patients undergoing treatment.
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The Internet of Things (IoT) applied to the treatment of cancer patients has been explored and the results are promising. This review aims to identify the applications and benefits of using IoT techniques, especially wearable devices, ...

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• Information theory directly measures test value as reduction in uncertainty.
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Clinicians order laboratory tests in an effort to reduce diagnostic or therapeutic uncertainty. Information theory provides the opportunity to quantify the degree to which a test result is expected to reduce ...

We may be suddenly forced to use crutches when having injuries to our legs, and, at that time, are often unfamiliar with the use of the crutches. To prevent secondary accidents that are caused by the lack of the patient’s knowledge of using ...