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Optimizing cardiovascular disease mortality prediction: a super learner approach in the tehran lipid and glucose study
Cardiovascular disease (CVD) is the most important cause of death in the world and has a potential impact on health care costs, this study aimed to evaluate the performance of machine learning survival models ... (Source: BMC Medical Informatics and Decision Making)
Source: BMC Medical Informatics and Decision Making - April 16, 2024 Category: Information Technology Authors: Parvaneh Darabi, Safoora Gharibzadeh, Davood Khalili, Mehrdad Bagherpour-Kalo and Leila Janani Tags: Research Source Type: research

Identifying subgroups in heart failure patients with multimorbidity by clustering and network analysis
This study presents a workflow for identifying and characterizing patients with Heart Failure (HF) and multimorbidity utilizing data from Electronic Health Records. Multimorbidity, the co-occurrence of two or ... (Source: BMC Medical Informatics and Decision Making)
Source: BMC Medical Informatics and Decision Making - April 15, 2024 Category: Information Technology Authors: Catarina Martins, Bernardo Neves, Andreia Sofia Teixeira, Miguel Froes, Pedro Sarmento, Jaime Machado, Carlos  A. Magalhães, Nuno A. Silva, Mário J. Silva and Francisca Leite Tags: Research Source Type: research

Decision support systems for antibiotic prescription in hospitals: a survey with hospital managers on factors for implementation
Inappropriate antimicrobial use, such as antibiotic intake in viral infections, incorrect dosing and incorrect dosing cycles, has been shown to be an important determinant of the emergence of antimicrobial res... (Source: BMC Medical Informatics and Decision Making)
Source: BMC Medical Informatics and Decision Making - April 15, 2024 Category: Information Technology Authors: Pinar Tokg öz, Stephan Krayter, Jessica Hafner and Christoph Dockweiler Tags: Research Source Type: research

Early prediction of sudden cardiac death risk with Nested LSTM based on electrocardiogram sequential features
Electrocardiogram (ECG) signals are very important for heart disease diagnosis. In this paper, a novel early prediction method based on Nested Long Short-Term Memory (Nested LSTM) is developed for sudden cardi... (Source: BMC Medical Informatics and Decision Making)
Source: BMC Medical Informatics and Decision Making - April 10, 2024 Category: Information Technology Authors: Ke Wang, Kai Zhang, Banteng Liu, Wei Chen and Meng Han Tags: Research Source Type: research

Machine learning pipeline to analyze clinical and proteomics data: experiences on a prostate cancer case
Proteomic-based analysis is used to identify biomarkers in blood samples and tissues. Data produced by devices such as mass spectrometry requires platforms to identify and quantify proteins (or peptides). Clin... (Source: BMC Medical Informatics and Decision Making)
Source: BMC Medical Informatics and Decision Making - April 8, 2024 Category: Information Technology Authors: Patrizia Vizza, Federica Aracri, Pietro Hiram Guzzi, Marco Gaspari, Pierangelo Veltri and Giuseppe Tradigo Tags: Research Source Type: research

Hybrid disease prediction approach leveraging digital twin and metaverse technologies for health consumer
Emerging from the convergence of digital twin technology and the metaverse, consumer health (MCH) is witnessing a transformative shift. The amalgamation of bioinformatics with healthcare Big Data has ushered i... (Source: BMC Medical Informatics and Decision Making)
Source: BMC Medical Informatics and Decision Making - April 5, 2024 Category: Information Technology Authors: Chaitanya Kulkarni, Aadam Quraishi, Mohan Raparthi, Mohammad Shabaz, Muhammad Attique Khan, Raj A. Varma, Ismail Keshta, Mukesh Soni and Haewon Byeon Tags: Research Source Type: research

Post-surgery survival and associated factors for cardiac patients in Ethiopia: applications of machine learning, semi-parametric and parametric modelling
Living in poverty, especially in low-income countries, are more affected by cardiovascular disease. Unlike the developed countries, it remains a significant cause of preventable heart disease in the Sub-Sahara... (Source: BMC Medical Informatics and Decision Making)
Source: BMC Medical Informatics and Decision Making - March 29, 2024 Category: Information Technology Authors: Melaku Tadege, Awoke Seyoum Tegegne and Zelalem G. Dessie Tags: Research Source Type: research

Correction: Developing an integrated clinical decision support system for the early identification and management of kidney disease —building cross-sectoral partnerships
(Source: BMC Medical Informatics and Decision Making)
Source: BMC Medical Informatics and Decision Making - March 28, 2024 Category: Information Technology Authors: Gillian Gorham, Asanga Abeyaratne, Sam Heard, Liz Moore, Pratish George, Paul Kamler, Sandawana William Majoni, Winnie Chen, Bhavya Balasubramanya, Mohammad Radwanur Talukder, Sophie Pascoe, Adam Whitehead, Cherian Sajiv, Louise Maple-Brown, Nadarajah Kan Tags: Correction Source Type: research

A novel generative adversarial networks modelling for the class imbalance problem in high dimensional omics data
Class imbalance remains a large problem in high-throughput omics analyses, causing bias towards the over-represented class when training machine learning-based classifiers. Oversampling is a common method used... (Source: BMC Medical Informatics and Decision Making)
Source: BMC Medical Informatics and Decision Making - March 28, 2024 Category: Information Technology Authors: Samuel Cusworth, Georgios V. Gkoutos and Animesh Acharjee Tags: Research Source Type: research

Robot-assisted surgery and artificial intelligence-based tumour diagnostics: social preferences with a representative cross-sectional survey
The aim of this study was to assess social preferences for two different advanced digital health technologies and investigate the contextual dependency of the preferences. (Source: BMC Medical Informatics and Decision Making)
Source: BMC Medical Informatics and Decision Making - March 27, 2024 Category: Information Technology Authors: Áron Hölgyesi, Zsombor Zrubka, László Gulácsi, Petra Baji, Tamás Haidegger, Miklós Kozlovszky, Miklós Weszl, Levente Kovács and Márta Péntek Tags: Research Source Type: research

A prediction model based on artificial intelligence techniques for disintegration time and hardness of fast disintegrating tablets in pre-formulation tests
The pharmaceutical industry is continually striving to innovate drug development and formulation processes. Orally disintegrating tablets (ODTs) have gained popularity due to their quick release and patient-fr... (Source: BMC Medical Informatics and Decision Making)
Source: BMC Medical Informatics and Decision Making - March 27, 2024 Category: Information Technology Authors: Mehri Momeni, Marziyeh Afkanpour, Saleh Rakhshani, Amin Mehrabian and Hamed Tabesh Tags: Research Source Type: research

Application of machine learning methods for predicting under-five mortality: analysis of Nigerian demographic health survey 2018 dataset
This study aimed to assess the effectiveness of various machine learning algorithms in predicting under-five mortality in... (Source: BMC Medical Informatics and Decision Making)
Source: BMC Medical Informatics and Decision Making - March 25, 2024 Category: Information Technology Authors: Oduse Samuel, Temesgen Zewotir and Delia North Tags: Research Source Type: research

Machine learning models for predicting the onset of chronic kidney disease after surgery in patients with renal cell carcinoma
Patients with renal cell carcinoma (RCC) have an elevated risk of chronic kidney disease (CKD) following nephrectomy. Therefore, continuous monitoring and subsequent interventions are necessary. It is recommen... (Source: BMC Medical Informatics and Decision Making)
Source: BMC Medical Informatics and Decision Making - March 22, 2024 Category: Information Technology Authors: Seol Whan Oh, Seok-Soo Byun, Jung Kwon Kim, Chang Wook Jeong, Cheol Kwak, Eu Chang Hwang, Seok Ho Kang, Jinsoo Chung, Yong-June Kim, Yun-Sok Ha and Sung-Hoo Hong Tags: Research Source Type: research

Multimodal deep learning-based diagnostic model for BPPV
Benign paroxysmal positional vertigo (BPPV) is a prevalent form of vertigo that necessitates a skilled physician to diagnose by observing the nystagmus and vertigo resulting from specific changes in the patien... (Source: BMC Medical Informatics and Decision Making)
Source: BMC Medical Informatics and Decision Making - March 21, 2024 Category: Information Technology Authors: Hang Lu, Yuxing Mao, Jinsen Li and Lin Zhu Tags: Research Source Type: research

An Effective Methodology for Scoring to Assist Emergency Physicians in Identifying Overcrowding in an Academic Emergency Department in Thailand
Emergency Department (ED) overcrowding is a global concern, with tools like NEDOCS, READI, and Work Score used as predictors. These tools aid healthcare professionals in identifying overcrowding and preventing... (Source: BMC Medical Informatics and Decision Making)
Source: BMC Medical Informatics and Decision Making - March 21, 2024 Category: Information Technology Authors: Sukumpat Na Nan, Borwon Wittayachamnankul, Wachira Wongtanasarasin, Theerapon Tangsuwanaruk, Krongkarn Sutham and Orawit Thinnukool Tags: Research Source Type: research