e.g. mhealth
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Skip search results from other journals and go to results- 2 JMIR Medical Education
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Herein, we detail how we, as the leaders of this collaborative, developed a group of women+ individuals and respective institutions across the BTAA; how we crafted the inaugural conference; and how we are actively conducting an environmental scan survey and planning continuity of programming through conference host handoff, sharing of materials, and webinars.
JMIR Form Res 2025;9:e65561
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While a plethora of high-quality web-based resources exist to teach programming skills and ML model development, there are few introductory curricula specifically tailored to medical students without a background in data science or programming. Additionally, there is little guidance provided to medical students on where to begin. Some medical societies do have AI outreach activities, but these are limited to trainees within their specialty [3-5].
JMIR Med Educ 2024;10:e46500
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Furthermore, scientists with limited knowledge of bioinformatics or programming may experience difficulty in analyzing SARS-Co V-2 genomes.
We developed the Co V-Seq toolkit to address these challenges. Co V-Seq consists of several components: a data analysis pipeline that takes FASTA sequences and generates variant callsets in variant call format (VCF) and open reading frame (ORF) predictions.
J Med Internet Res 2020;22(10):e22299
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Medical Student Training in eHealth: Scoping Review
Notably, AI and the Io T were only studied in a No Intervention manner, although programming was always studied through interventions.
Number of included articles by year of publication and presence of an intervention.
Number of articles discussing each aspect of e Health. AI: artificial intelligence; Io T: internet of things.
Of the 20 papers that studied a population of medical students, 11 (55%) had a sample size of more than 100.
JMIR Med Educ 2020;6(2):e20027
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In this study, C language programming was used to implement data feature extraction based on the Markov model. It was then used to programmatically realize speech recognition for specific speech instances, as well as write speech recognition functions into functions that can be called by other modules. Additionally, it was used to implement a speech recognition system foundation, and to cultivate and improve the ability of the system to consult the literature and comprehensively use new knowledge [1].
JMIR Med Inform 2020;8(6):e18677
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The development of the DMT applied lessons from an existing tool developed for the Australian food guidance system (AFGS) that used a linear programming approach to modeling. Algorithms published as part of the AFGS were used as the basis for developing the DMT using nonlinear modeling. Constraint optimization was also used to ensure the DMT was suited to developing individual dietary prescriptions that are needed in dietary intervention trials as the AFGS targeted population groups.
J Med Internet Res 2016;18(7):e190
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