Artificial Intelligence in Medicine Artificial Intelligence in Medicine RSS feedThis is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

Editorial Board
Publication date: March 2020Source: Artificial Intelligence in Medicine, Volume 103Author(s): (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - March 3, 2020 Category: Bioinformatics Source Type: research

Characterizing the critical features when personalizing antihypertensive drugs using spectrum analysis and machine learning methods
Publication date: Available online 29 February 2020Source: Artificial Intelligence in MedicineAuthor(s): Liu Chunyu, Liu Ran, Zhou Junteng, Wang Miye, Xu Jing, Su Lan, Zuo Yixuan, Zhang Rui, Feng Yizhou, Wang Chen, Yan Hongmei, Zhang Qing (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - March 1, 2020 Category: Bioinformatics Source Type: research

Detecting Potential Signals of Adverse Drug Events from Prescription Data
Publication date: Available online 27 February 2020Source: Artificial Intelligence in MedicineAuthor(s): Chen Zhan, Elizabeth Roughead, Lin Liu, Nicole Pratt, Jiuyong Li (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 28, 2020 Category: Bioinformatics Source Type: research

Offline identification of surgical deviations in laparoscopic rectopexy
Publication date: Available online 27 February 2020Source: Artificial Intelligence in MedicineAuthor(s): Arnaud Huaulmé, Sandrine Voros, Fabian Reche, Jean-Luc Faucheron, Alexandre Moreau-Gaudry, Pierre Jannin (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 28, 2020 Category: Bioinformatics Source Type: research

A neutrosophic-entropy based adaptive thresholding segmentation algorithm: A special application in MR images of Parkinson's disease
Publication date: Available online 28 February 2020Source: Artificial Intelligence in MedicineAuthor(s): Pritpal Singh (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 28, 2020 Category: Bioinformatics Source Type: research

A Novel Deep Mining Model for Effective Knowledge Discovery from Omics Data
Publication date: Available online 24 February 2020Source: Artificial Intelligence in MedicineAuthor(s): Abeer Alzubaidi, Jonathan Tepper, Ahmad lotfi (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 25, 2020 Category: Bioinformatics Source Type: research

Toward Development of PreVoid Alerting System for Nocturnal Enuresis Patients: A Fuzzy-Based Approach for Determining the Level of Liquid Encased in Urinary Bladder
This study aims to develop a machine-learning empowered technique to quantify to what extent an individual's bladder is filled by observing the filling-voiding pattern of a patient over a training period. In this experiment, a pulse-echo sonar element is used to generate ultrasound pulses while the probe surface is positioned perpendicular to the bladder's position. From the reflected echoes, four features which show sufficient sensitiveness and therefore could be modulated noticeably by different levels of liquid encased in the bladder, are extracted. The extracted features are then fed into a novel intelligent decision s...
Source: Artificial Intelligence in Medicine - February 23, 2020 Category: Bioinformatics Source Type: research

Automated Machine Learning: Review of the State-of-the-Art and Opportunities for Healthcare
ConclusionWhile there have already been some use cases of AutoML in the healthcare field, more work needs to be done in order for there to be widespread adoption of AutoML in healthcare. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 22, 2020 Category: Bioinformatics Source Type: research

Reinforcement Learning Application in Diabetes Blood Glucose Control: A Systematic Review
ConclusionsThe advances in health technologies and mobile devices have facilitated the implementation of RL algorithms for optimal glycemic regulation in diabetes. However, there exists few articles in the literature focused on the application of these algorithms to the BG regulation problem. Moreover, such algorithms are designed for control tasks as BG adjustment and their use have increased recently in the diabetes research area, therefore we foresee RL algorithms will be used more frequently for BG control in the coming years. Furthermore, in the literature there is a lack of focus on aspects that influence BG level su...
Source: Artificial Intelligence in Medicine - February 22, 2020 Category: Bioinformatics Source Type: research

Wearable sensor-based evaluation of psychosocial stress in patients with Metabolic Syndrome
This study presents a multivariate methodology for the modeling of stress on metabolic syndrome (MES) patients. We have developed a supporting system to cope with MES patients’ anxiety and stress by means of several biosignals such as ECG, GSR, body temperature, SPO2, glucose level, and blood pressure that are measured by a wearable device. We employed a neural network model to classify emotions with HRV analysis in the detection of stressor moments. We have accurately recognized the stressful situations using physiological responses to stimuli by utilizing our proposed affective state detection algorithm. We evaluated o...
Source: Artificial Intelligence in Medicine - February 22, 2020 Category: Bioinformatics Source Type: research

Multimodal Data Analysis of Epileptic EEG and rs-fMRI via Deep Learning and Edge Computing
ConclusionsThe combination of rs-fMRI and EEG/iEEG can reveal more information about dynamic functional connectivity. However, simultaneous fMRI and EEG data acquisition present challenges. We have proposed system models for leveraging and processing independently acquired fMRI and EEG data. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 20, 2020 Category: Bioinformatics Source Type: research

Feature Selection based Multivariate Time Series Forecasting: An Application to Antibiotic Resistance Outbreaks Prediction
Publication date: Available online 19 February 2020Source: Artificial Intelligence in MedicineAuthor(s): Fernando Jiménez, José Palma, Gracia Sánchez, David Marín, Francisco Palacios, M.D, Lucía López, M.DAbstractAntimicrobial resistance has become one of the most important health problems and global action plans have been proposed globally. Prevention plays a key role in these actions plan and, in this context, we propose the use of Artificial Intelligence, specifically Time Series Forecasting techniques, for predicting future outbreaks of Methicilin-resistant Staphylococcus aereus (MRSA). Infection incidence foreca...
Source: Artificial Intelligence in Medicine - February 19, 2020 Category: Bioinformatics Source Type: research

Early detection of sepsis utilizing deep learning on electronic health record event sequences
Conclusion: We present a deep learning system for early detection of sepsis that can learn characteristics of the key factors and interactions from the raw event sequence data itself, without relying on a labor-intensive feature extraction work. Our system outperforms baseline models, such as gradient boosting, which rely on specific data elements and therefore suffer from many missing values in our dataset. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 19, 2020 Category: Bioinformatics Source Type: research

A recurrent neural network approach to predicting hemoglobin trajectories in patients with End-Stage Renal Disease
Publication date: Available online 19 February 2020Source: Artificial Intelligence in MedicineAuthor(s): Benjamin Lobo, Emaad Abdel-Rahman, Donald Brown, Lori Dunn, Brendan BowmanAbstractThe most severe form of kidney disease, End-Stage Renal Disease (ESRD) is treated with various forms of dialysis – artificial blood cleansing. Dialysis patients suffer many health burdens including high mortality and hospitalization rates, and symptomatic anemia: a low red blood cell count as indicated by a low hemoglobin (Hgb) level. ESRD-induced anemia is treated, with variable patient response, by erythropoiesis stimulating agents (ES...
Source: Artificial Intelligence in Medicine - February 19, 2020 Category: Bioinformatics Source Type: research

Efficient Treatment of Outliers and Class Imbalance for Diabetes Prediction
Publication date: Available online 10 February 2020Source: Artificial Intelligence in MedicineAuthor(s): Nonso Nnamoko, Ioannis KorkontzelosAbstractLearning from outliers and imbalanced data remains one of the major difficulties for machine learning classifiers. Among the numerous techniques dedicated to tackle this problem, data preprocessing solutions are known to be efficient and easy to implement. In this paper, we propose a selective data preprocessing approach that embeds knowledge of the outlier instances into artificially generated subset to achieve an even distribution. The synthetic minority oversampling techniqu...
Source: Artificial Intelligence in Medicine - February 11, 2020 Category: Bioinformatics Source Type: research