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Real-world data medical knowledge graph: construction and applications
ConclusionThe established systematic procedure can efficiently construct a high-quality medical KG from large-scale EMRs. The proposed ranking function PSR achieves the best performance under all relations, and the disease clustering result validates the efficacy of the learned embedding vector as entity’s semantic representation. Moreover, the obtained KG finds many successful applications due to its statistics-based quadruplet.where Ncomin is a minimum co-occurrence number and R is the basic reliability value. The reliability value can measure how reliable is the relationship between Si and Oij. The reason for the defi...
Source: Artificial Intelligence in Medicine - February 7, 2020 Category: Bioinformatics Source Type: research

Automatic computation of mandibular indices in dental panoramic radiographs for early osteoporosis detection
CONCLUSIONSThe proposed approach provides an automatic procedure able to process with efficiency and reliability panoramic X-Ray images for early osteoporosis detection. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 6, 2020 Category: Bioinformatics Source Type: research

A multicenter random forest model for effective prognosis prediction in collaborative clinical research network
ConclusionThe proposed random forest model exhibits ideal prediction capability using multicenter clinical data and overcomes the performance limitation arising from privacy guarantees. It can also provide feature importance ranking across institutions without pooling the data at a central site. This study offers a practical solution for building a prognosis prediction model in the collaborative clinical research network and solves practical issues in real-world applications of medical artificial intelligence. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 6, 2020 Category: Bioinformatics Source Type: research

Random Forest Enhancement using Improved Artificial Fish Swarm for the Medial Knee Contact Force Prediction
Publication date: Available online 3 February 2020Source: Artificial Intelligence in MedicineAuthor(s): Yean Zhu, Weiyi XU, Guoliang Luo, Haolun Wang, Jingjing Yang, Wei LuAbstractKnee Contact Force (KCF) is an important factor to evaluate the knee joint function for the patients with knee joint impairment. However, the KCF measurement based on the instrumented prosthetic implants or inverse dynamics analysis is limited due to the invasive, expensive price and time consumption. In this work, we propose a KCF prediction method by integrating the artificial fish swarm and the random forest algorithm. First, we train a random...
Source: Artificial Intelligence in Medicine - February 4, 2020 Category: Bioinformatics Source Type: research

An Incremental Explanation of Inference in Bayesian Networks for Increasing Model Trustworthiness and Supporting Clinical Decision Making
Publication date: Available online 31 January 2020Source: Artificial Intelligence in MedicineAuthor(s): Evangelia Kyrimi, Somayyeh Mossadegh, Nigel Tai, William MarshAbstractVarious AI models are increasingly being considered as part of clinical decision-support tools. However, the trustworthiness of such models is rarely considered. Clinicians are more likely to use a model if they can understand and trust its predictions. Key to this is if its underlying reasoning can be explained. A Bayesian network (BN) model has the advantage that it is not a black-box and its reasoning can be explained. In this paper, we propose an i...
Source: Artificial Intelligence in Medicine - February 1, 2020 Category: Bioinformatics Source Type: research

Mixed-Integer Optimization Approach to Learning Association Rules for Unplanned ICU Transfer
In this study, we present a new decision tool using a mathematical optimization approach aiming to automatically discover rules associating diagnostic features with high-risk outcome (i.e., unplanned transfers) in different deterioration scenarios. We consider four mutually exclusive patient subgroups based on the principal reasons of ED visits: infections, cardiovascular/respiratory diseases, gastrointestinal diseases, and neurological/other diseases at a suburban teaching hospital. The analysis results demonstrate significant rules associated with unplanned transfer outcome for each subgroups and also show comparable pre...
Source: Artificial Intelligence in Medicine - February 1, 2020 Category: Bioinformatics Source Type: research

Retraction notice to “Diagnosis Labeling with Disease-Specific Characteristics Mining” [Artif. Intell. Med. 90 (2018) 25–33]
Publication date: Available online 27 January 2020Source: Artificial Intelligence in MedicineAuthor(s): Jun Guo, Xuan Yuan, Xia Zheng, Xu Pengfei, Yun Xiao, Baoying Liu (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - January 29, 2020 Category: Bioinformatics Source Type: research

Quantitative knowledge presentation models of Traditional Chinese Medicine (TCM): A review
Publication date: Available online 24 January 2020Source: Artificial Intelligence in MedicineAuthor(s): Xiaoli Chu, Bingzhen Sun, Qingchun Huang, Shouping Peng, Yingyan Zhou, Yan ZhangAbstractModern computer technology sheds light on new ways of innovating Traditional Chinese Medicine (TCM). One method that gets increasing attention is the quantitative research method, which makes use of data mining and artificial intelligence technology as well as the mathematical principles in the research on rationales, academic viewpoints of famous doctors of TCM, dialectical treatment by TCM, clinical technology of TCM, the patterns o...
Source: Artificial Intelligence in Medicine - January 26, 2020 Category: Bioinformatics Source Type: research

Classification of glomerular hypercellularity using convolutional features and support vector machine
Publication date: Available online 25 January 2020Source: Artificial Intelligence in MedicineAuthor(s): Paulo Chagas, Luiz Souza, Ikaro Araújo, Nayze Aldeman, Angelo Duarte, Michele Angelo, Washington LC dos-Santos, Luciano OliveiraAbstractGlomeruli are histological structures of the kidney cortex formed by interwoven blood capillaries, and are responsible for blood filtration. Glomerular lesions impair kidney filtration capability, leading to protein loss and metabolic waste retention. An example of lesion is the glomerular hypercellularity, which is characterized by an increase in the number of cell nuclei in different ...
Source: Artificial Intelligence in Medicine - January 26, 2020 Category: Bioinformatics Source Type: research

Batch Mode Active Learning on the Riemannian Manifold for Automated Scoring of Nuclear Pleomorphism in Breast Cancer
Publication date: Available online 25 January 2020Source: Artificial Intelligence in MedicineAuthor(s): Asha Das, Madhu S. Nair, David Peter S.AbstractBreast cancer is the most prevalent invasive type of cancer among women. The mortality rate of the disease can be reduced considerably through timely prognosis and felicitous treatment planning, by utilizing the computer aided detection and diagnosis techniques. With the advent of whole slide image (WSI) scanners for digitizing the histopathological tissue samples, there is a drastic increase in the availability of digital histopathological images. However, these samples are...
Source: Artificial Intelligence in Medicine - January 26, 2020 Category: Bioinformatics Source Type: research

Editorial Board
Publication date: January 2020Source: Artificial Intelligence in Medicine, Volume 102Author(s): (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - January 23, 2020 Category: Bioinformatics Source Type: research

Prognostic Factors of Rapid Symptoms Progression in Patients with Newly Diagnosed Parkinson’s Disease
Publication date: Available online 21 January 2020Source: Artificial Intelligence in MedicineAuthor(s): Kostas M. Tsiouris, Spiros Konitsiotis, Dimitrios D. Koutsouris, Dimitrios I. FotiadisAbstractTracking symptoms progression in the early stages of Parkinson’s disease (PD) is a laborious endeavor as the disease can be expressed with vastly different phenotypes, forcing clinicians to follow a multi-parametric approach in patient evaluation, looking for not only motor symptomatology but also non-motor complications, including cognitive decline, sleep problems and mood disturbances. Being neurodegenerative in nature, PD i...
Source: Artificial Intelligence in Medicine - January 23, 2020 Category: Bioinformatics Source Type: research

Scalogram based Prediction Model for Respiratory disorders using Optimized Convolutional Neural Networks
Publication date: Available online 20 January 2020Source: Artificial Intelligence in MedicineAuthor(s): S. Jayalakshmy, Gnanou Florence SudhaAbstractAuscultation of the lung is a conventional technique used for diagnosing chronic obstructive pulmonary diseases (COPDs) and lower respiratory infections and disorders in patients. In most of the earlier works, wavelet transforms or spectrograms have been used to analyze the lung sounds. However, an accurate prediction model for respiratory disorders has not been developed so far. In this paper, a pre-trained optimized Alexnet Convolutional Neural Network (CNN) architecture is ...
Source: Artificial Intelligence in Medicine - January 21, 2020 Category: Bioinformatics Source Type: research

Comprehensive electrocardiographic diagnosis based on deep learning
Publication date: Available online 20 January 2020Source: Artificial Intelligence in MedicineAuthor(s): Oh Shu Lih, V Jahmunah, Tan Ru San, Edward J Ciaccio, Toshitaka Yamakawa, Masayuki Tanabe, Makiko Kobayashi, Oliver Faust, U Rajendra AcharyaAbstractCardiovascular disease (CVD) is the leading cause of death worldwide, and coronary artery disease (CAD) is a major contributor. Early-stage CAD can progress if undiagnosed and left untreated, leading to myocardial infarction (MI) that may induce irreversible heart muscle damage, resulting in heart chamber remodeling and eventual congestive heart failure (CHF). Electrocardiog...
Source: Artificial Intelligence in Medicine - January 21, 2020 Category: Bioinformatics Source Type: research

Comprehensive analysis of rule formalisms to represent clinical guidelines: Selection criteria and case study on antibiotic clinical guidelines
ConclusionsThe proposed framework of criteria may help clinical institutions to select the most suitable rule technology for the representation of CGs in general, and for the antibiotic prescription domain in particular, depicting the main aspects that lead to Computer Interpretable Guidelines (CIGs), such as Logic expressivity (Open/Closed World Assumption, Negation-As-Failure), Temporal Reasoning and Interoperability with existing HIS and clinical workflow. Future work will focus on providing clinicians with suggestions regarding new potential steps for CGs, considering process mining approaches and CGs Process Workflows...
Source: Artificial Intelligence in Medicine - January 18, 2020 Category: Bioinformatics Source Type: research