It Is in Our DNA: Bringing Electronic Health Records and Genomic Data Together for Precision Medicine
JMIR Bioinformatics and Biotechnology
by Alan J Robertson, Andrew J Mallett, Zornitza Stark, Clair Sullivan
1M ago
Health care is at a turning point. We are shifting from protocolized medicine to precision medicine, and digital health systems are facilitating this shift. By providing clinicians with detailed information for each patient and analytic support for decision-making at the point of care, digital health technologies are enabling a new era of precision medicine. Genomic data also provide clinicians with information that can improve the accuracy and timeliness of diagnosis, optimize prescribing, and target risk reduction strategies, all of which are key elements for precision medicine. However, gen ..read more
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ChatGPT and Medicine: Together We Embrace the AI Renaissance
JMIR Bioinformatics and Biotechnology
by Sean Hacking
2M ago
The generative artificial intelligence (AI) model ChatGPT holds transformative prospects in medicine. The development of such models has signaled the beginning of a new era where complex biological data can be made more accessible and interpretable. ChatGPT is a natural language processing tool that can process, interpret, and summarize vast data sets. It can serve as a digital assistant for physicians and researchers, aiding in integrating medical imaging data with other multiomics data and facilitating the understanding of complex biological systems. The physician’s and AI’s viewpoints empha ..read more
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Machine Learning Models for Prediction of Maternal Hemorrhage and Transfusion: Model Development Study
JMIR Bioinformatics and Biotechnology
by Homa Khorrami Ahmadzia, Alexa C Dzienny, Mike Bopf, Jaclyn M Phillips, Jerome Jeffrey Federspiel, Richard Amdur, Madeline Murguia Rice, Laritza Rodriguez
5M ago
Background: Current postpartum hemorrhage (PPH) risk stratification is based on traditional statistical models or expert opinion. Machine learning could optimize PPH prediction by allowing for more complex modeling. Objective: We sought to improve PPH prediction and compare machine learning and traditional statistical methods. Methods: We developed models using the Consortium for Safe Labor data set (2002-2008) from 12 US hospitals. The primary outcome was a transfusion of blood products or PPH (estimated blood loss of ≥1000 mL). The secondary outcome was a transfusion of any blood product. Fi ..read more
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User and Usability Testing of a Web-Based Genetics Education Tool for Parkinson Disease: Mixed Methods Study
JMIR Bioinformatics and Biotechnology
by Noah Han, Rachel A Paul, Tanya Bardakjian, Daniel Kargilis, Angela R Bradbury, Alice Chen-Plotkin, Thomas F Tropea
11M ago
Background: Genetic testing is essential to identify research participants for clinical trials enrolling people with Parkinson disease (PD) carrying a variant in the glucocerebrosidase (GBA) or leucine-rich repeat kinase 2 (LRRK2) genes. The limited availability of professionals trained in neurogenetics or genetic counseling is a major barrier to increased testing. Telehealth solutions to increase access to genetics education can help address issues around counselor availability and offer options to patients and family members. Objective: As an alternative to pretest genetic counseling, we dev ..read more
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Secure Comparisons of Single Nucleotide Polymorphisms Using Secure Multiparty Computation: Method Development
JMIR Bioinformatics and Biotechnology
by Andrew Woods, Skyler T Kramer, Dong Xu, Wei Jiang
1y ago
Background: While genomic variations can provide valuable information for health care and ancestry, the privacy of individual genomic data must be protected. Thus, a secure environment is desirable for a human DNA database such that the total data are queryable but not directly accessible to involved parties (eg, data hosts and hospitals) and that the query results are learned only by the user or authorized party. Objective: In this study, we provide efficient and secure computations on panels of single nucleotide polymorphisms (SNPs) from genomic sequences as computed under the following set ..read more
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Mutations of SARS-CoV-2 Structural Proteins in the Alpha, Beta, Gamma, and Delta Variants: Bioinformatics Analysis
JMIR Bioinformatics and Biotechnology
by Saima Rehman Khetran, Roma Mustafa
1y ago
Background: COVID-19 and Middle East Respiratory Syndrome are two pandemic respiratory diseases caused by coronavirus species. The novel disease COVID-19 caused by SARS-CoV-2 was first reported in Wuhan, Hubei Province, China, in December 2019, and became a pandemic within 2-3 months, affecting social and economic platforms worldwide. Despite the rapid development of vaccines, there have been obstacles to their distribution, including a lack of fundamental resources, poor immunization, and manual vaccine replication. Several variants of the original Wuhan strain have emerged in the last 3 year ..read more
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Introducing JMIR Bioinformatics and Biotechnology: A Platform for Interdisciplinary Collaboration and Cutting-Edge Research
JMIR Bioinformatics and Biotechnology
by Ece Dilber Gamsiz Uzun
1y ago
JMIR Bioinformatics and Biotechnology supports interdisciplinary research and welcomes contributions that push the boundaries of bioinformatics, genomics, artificial intelligence, and pathology informatics ..read more
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Genomic Insights Into the Evolution and Demographic History of the SARS-CoV-2 Omicron Variant: Population Genomics Approach
JMIR Bioinformatics and Biotechnology
by Kritika M Garg, Vinita Lamba, Balaji Chattopadhyay
1y ago
Background: A thorough understanding of the patterns of genetic subdivision in a pathogen can provide crucial information that is necessary to prevent disease spread. For SARS-CoV-2, the availability of millions of genomes makes this task analytically challenging, and traditional methods for understanding genetic subdivision often fail. Objective: The aim of our study was to use population genomics methods to identify the subtle subdivisions and demographic history of the Omicron variant, in addition to those captured by the Pango lineage. Methods: We used a combination of an evolutionary netw ..read more
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Decision of the Optimal Rank of a Nonnegative Matrix Factorization Model for Gene Expression Data Sets Utilizing the Unit Invariant Knee Method: Development and Evaluation of the Elbow Method for Rank Selection
JMIR Bioinformatics and Biotechnology
by Emine Guven
1y ago
Background: There is a great need to develop a computational approach to analyze and exploit the information contained in gene expression data. The recent utilization of nonnegative matrix factorization (NMF) in computational biology has demonstrated the capability to derive essential details from a high amount of data in particular gene expression microarrays. A common problem in NMF is finding the proper number rank (r) of factors of the degraded demonstration, but no agreement exists on which technique is most appropriate to utilize for this purpose. Thus, various techniques have been sugge ..read more
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The Identification of Potential Drugs for Dengue Hemorrhagic Fever: Network-Based Drug Reprofiling Study
JMIR Bioinformatics and Biotechnology
by Praveenkumar Kochuthakidiyel Suresh, Gnanasoundari Sekar, Kavya Mallady, Wan Suriana Wan Ab Rahman, Wan Nazatul Shima Shahidan, Gokulakannan Venkatesan
1y ago
Background: Dengue fever can progress to dengue hemorrhagic fever (DHF), a more serious and occasionally fatal form of the disease. Indicators of serious disease arise about the time the fever begins to reduce (typically 3 to 7 days following symptom onset). There are currently no effective antivirals available. Drug repurposing is an emerging drug discovery process for rapidly developing effective DHF therapies. Through network pharmacology modeling, several US Food and Drug Administration (FDA)-approved medications have already been researched for various viral outbreaks. Objective: We aimed ..read more
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