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Deep-kidney: an effective deep learning framework for chronic kidney disease prediction
AbstractChronic kidney disease (CKD) is one of today ’s most serious illnesses. Because this disease usually does not manifest itself until the kidney is severely damaged, early detection saves many people’s lives. Therefore, the contribution of the current paper is proposing three predictive models to predict CKD possible occurrence within 6 or 1 2 months before disease existence namely; convolutional neural network (CNN), long short-term memory (LSTM) model, and deep ensemble model. The deep ensemble model fuses three base deep learning classifiers (CNN, LSTM, and LSTM-BLSTM) using majority voting technique. To evalu...
Source: Health Information Science and Systems - December 1, 2023 Category: Information Technology Source Type: research

Multi-omics prognostic signatures of IPO11 mRNA expression and clinical outcomes in colorectal cancer using bioinformatics approaches
AbstractThe most prevalent malignant illness of the gastrointestinal system, colorectal cancer, is the third most prevalent cancer in males and the second most prevalent cancer in women. Importin-11 is a protein that acts as a regulator of cancer cell proliferation in colorectal tumours by conveying\(\beta\)-catenin to the cell nucleus. However, the IPO11 gene was found to encode a protein called Importin-11, which functions as a nucleus importer for the cell. As a result, preventing\(\beta\)-catenin from entering the nucleus requires blocking Importin-11. As a result, we conducted a multi-omics investigation to assess IPO...
Source: Health Information Science and Systems - November 27, 2023 Category: Information Technology Source Type: research

CLAD-Net: cross-layer aggregation attention network for real-time endoscopic instrument detection
AbstractAs medical treatments continue to advance rapidly, minimally invasive surgery (MIS) has found extensive applications across various clinical procedures. Accurate identification of medical instruments plays a vital role in comprehending surgical situations and facilitating endoscopic image-guided surgical procedures. However, the endoscopic instrument detection poses a great challenge owing to the narrow operating space, with various interfering factors (e.g. smoke, blood, body fluids) and inevitable issues (e.g. mirror reflection, visual obstruction, illumination variation) in the surgery. To promote surgical effic...
Source: Health Information Science and Systems - November 27, 2023 Category: Information Technology Source Type: research

Automated lead toxicity prediction using computational modelling framework
ConclusionThe built prediction model can be beneficial in improving the point of care and hence reducing the cost and the risk involved. It is envisaged that in future, the proposed methodology will become a part of a screening process to assist healthcare experts at the point of evaluating the lead toxicity level in pregnant women. Women screened positive could be given a range of facilities including preliminary counselling to being referred  to the health centre for further diagnosis. Steps could be taken to reduce maternal lead exposure; hence, it could also be possible to mitigate the infant’s lead exposure by redu...
Source: Health Information Science and Systems - November 20, 2023 Category: Information Technology Source Type: research

Interrelated feature selection from health surveys using domain knowledge graph
AbstractFinding patterns among risk factors and chronic illness can suggest similar causes, provide guidance to improve healthy lifestyles, and give clues for possible treatments for outliers. Prior studies have typically isolated data challenges from single-disease datasets. However, the predictive power of multiple diseases is more helpful in establishing a healthy lifestyle than investigating one disease. Most studies typically focus on single-disease datasets; however, to ensure that health advice is generalized and contemporary, the features that predict the likelihood of many diseases can improve health advice effect...
Source: Health Information Science and Systems - November 16, 2023 Category: Information Technology Source Type: research

Essential proteins discovery based on dominance relationship and neighborhood similarity centrality
In this study, a purified PPI network is firstly introduced to reduce the impact of false positives in the PPI network. Secondly, by analyzing the similarity relationship between a protein and its neighbors in the PPI network, a new centrality called neighborhood similarity centrality (NSC) is proposed. Thirdly, based on the subcellular localization and orthologous data, the protein subcellular localization score and ortholog score are calculated, respectively. Fourthly, by analyzing a large number of methods based on multi-feature fusion, it is found that there is a special relationship among features, which is called dom...
Source: Health Information Science and Systems - November 16, 2023 Category: Information Technology Source Type: research

EAPR: explainable and augmented patient representation learning for disease prediction
AbstractPatient representation learning aims to encode meaningful information about the patient ’s Electronic Health Records (EHR) in the form of a mathematical representation. Recent advances in deep learning have empowered Patient representation learning methods with greater representational power, allowing the learned representations to significantly improve the performance of disease pre diction models. However, the inherent shortcomings of deep learning models, such as the need for massive amounts of labeled data and inexplicability, limit the performance of deep learning-based Patient representation learning method...
Source: Health Information Science and Systems - November 14, 2023 Category: Information Technology Source Type: research

ADHD-KG: a knowledge graph of attention deficit hyperactivity disorder
ConclusionThe Knowledge Graph of ADHD can provide valuable assistance to researchers and clinicians in the research, training, diagnostic and treatment processes for ADHD. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - November 11, 2023 Category: Information Technology Source Type: research

Liver fibrosis MR images classification based on higher-order interaction and sample distribution rebalancing
AbstractThe fractal features of liver fibrosis MR images exhibit an irregular fragmented distribution, and the diffuse feature distribution lacks interconnectivity, result- ing in incomplete feature learning and poor recognition accuracy. In this paper, we insert recursive gated convolution into the ResNet18 network to introduce spatial information interactions during the feature learning process and extend it to higher orders using recursion. Higher-order spatial information interactions enhance the correlation between features and enable the neural network to focus more on the pixel-level dependencies, enabling a global ...
Source: Health Information Science and Systems - November 8, 2023 Category: Information Technology Source Type: research

Predicting drug –drug interactions based on multi-view and multichannel attention deep learning
AbstractPredicting drug-drug interactions (DDIs) has become a major concern in the drug research field because it helps explore the pharmacological function of drugs and enables the development of new therapeutic drugs. Existing prediction methods simply integrate multiple drug attributes or perform tasks on a biomedical knowledge graph (KG). Though effective, few methods can fully utilize multi-source drug data information. In this paper, a multi-view and multichannel attention deep learning (MMADL) model is proposed, which not only extracts rich drug features containing both drug attributes and drug-related entity inform...
Source: Health Information Science and Systems - November 6, 2023 Category: Information Technology Source Type: research

Thyroidkeeper: a healthcare management system for patients with thyroid diseases
AbstractThyroid diseases, especially thyroid tumors, have a huge population in China. The postoperative patients, under China ’s incomplete tertiary diagnosis and treatment system, will frequently go to tertiary hospitals for follow-up and medication adjustment, resulting in heavy burdens on both specialists and patients. To help postoperative patients recover better against the above adverse conditions, a novel mobile a pplication ThyroidKeeper is proposed as a collaborative AI-based platform that benefits both patients and doctors. In addition to routine health records and management functions, ThyroidKeeper has achiev...
Source: Health Information Science and Systems - October 17, 2023 Category: Information Technology Source Type: research

Federated machine learning for predicting acute kidney injury in critically ill patients: a multicenter study in Taiwan
ConclusionA reliable prediction model for AKI in ICU patients was developed with a lead time of 24  h, and it performed better when the novel FL platform across hospitals was implemented. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - October 9, 2023 Category: Information Technology Source Type: research

A new segment method for pulmonary artery and vein
This study presents a new approach that leverages grayscale differences between A/V. Distinctions are measured using median and mean grayscale values within the vessel area. Initially, adherent regions are removed based on vessel structure. The trunk regions are segmented using gray level information near the heart region of the lung boundary. Incorrectly segmented vessels are corrected based on connectivity. For distal lung vessels, a similar distance field is established using a graph-cut method. Experimental results show the algorithm ’s superior segmentation accuracy, achieving 97.26% compared to the CNN-based averag...
Source: Health Information Science and Systems - October 6, 2023 Category: Information Technology Source Type: research

M-MSSEU: source-free domain adaptation for multi-modal stroke lesion segmentation using shadowed sets and evidential uncertainty
AbstractDue to the unavailability of source domain data encountered in unsupervised domain adaptation, there has been an increasing number of studies on source-free domain adaptation (SFDA) in recent years. To better solve the SFDA problem and effectively leverage the multi-modal information in medical images, this paper presents a novel SFDA method for multi-modal stroke lesion segmentation in which evidential deep learning instead of convolutional neural network. Specifically, for multi-modal stroke images, we design a multi-modal opinion fusion module which uses Dempster-Shafer evidence theory for decision fusion of dif...
Source: Health Information Science and Systems - September 28, 2023 Category: Information Technology Source Type: research

An error-bounded median filter for correcting ECG baseline wander
AbstractThe baseline wander (BLW) in electrocardiogram (ECG) is a common disturbance that has a significant influence on the ECG wave pattern recognition. Many methods, such as IIR filter, mean filter, etc., can be used to correct BLW; However, most of them work on the original ECG signals. Compressed ECG data are economic for data storage and transmission, and if the baseline correction can be processed on them, it will be more efficient than we decompress them first and then do such correction. In this paper, we propose a new type of median filterCM_Filter, which works on the synopses of straight lines achieved from ECG ...
Source: Health Information Science and Systems - September 26, 2023 Category: Information Technology Source Type: research