e.g. mhealth
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Skip search results from other journals and go to results- 7 Journal of Medical Internet Research
- 5 JMIR Formative Research
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Laboratory testing plays a key role in clinical decision-making and physician orders for laboratory tests are increasing [1,2]. It is estimated that at least 20% of the 4-5 billion lab orders submitted annually in the United States are inappropriate. Studies have shown that overutilization and underutilization of laboratory tests occur 20.6% and 44.8% of the time, respectively [3].
Interact J Med Res 2025;14:e46007
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The Clinicians’ Guide to Large Language Models: A General Perspective With a Focus on Hallucinations
Questions regarding overreliance on LLMs and other AI tools, as well as the legal and ethical ramifications of decision-making based upon AI input, are crucial. In the era of evidence-based medicine, LLM source material and information traceability will be essential in order to reliably inform patient care decisions. The value of the clinician’s experience in nuancing the LLM’s outputs will also remain critical in delivering personalized patient care.
Interact J Med Res 2025;14:e59823
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These features mean that participants can be more engaged in the decision-making process and aware of the broader significance of their contribution to the project, thus theoretically fostering greater satisfaction and retention when taking part in clinical trials [4,16,21].
JMIR Form Res 2024;8:e57165
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Markerless Motion Capture to Quantify Functional Performance in Neurodegeneration: Systematic Review
MMC can provide digitally measured functional performance data that could be used to enhance clinical decision-making and remote monitoring; identify risks such as falls; and better capture the impact of rehabilitative, pharmacological, and surgical interventions.
JMIR Aging 2024;7:e52582
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To address these challenges, a variety of freely available, patient-centered diagnostic decision support systems (DDSSs) have emerged and are increasingly being used by the general public [5] and patients with IRDs [6]. These DDSSs offer disease suggestions and advice for action within a few minutes and without any health care provider contact.
Rheport [7] is a web-based rheumatology referral system used in Germany to automatically triage appointments of new patients according to IRD probability [8,9].
J Med Internet Res 2024;26:e55542
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Process redesign will be facilitated by two partnership tools: (1) a 1-page visit preparation guide given to relevant patients by clinic staff before seeing the provider, with the intention to improve communication and shared decision-making, and (2) a library of short educational videos that clinic staff encourage patients to watch on medication safety.
JMIR Res Protoc 2024;13:e57878
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To investigate the potential association between the decision to upload the medical report and the independent variables disease-specific stigma and time course, we first performed a logistic regression (Hosmer-Lemeshow R2=0.319, Nagelkerke R2=0.590, Cox-Snell R2=0.537; χ215=86.973; P
To examine the association between the decision to upload and the independent variables stigma potential and time course, we performed a logistic regression controlling for the covariate intention to use (Hosmer-Lemeshow R2=0.289
JMIR Hum Factors 2024;11:e52625
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While myriad frameworks exist for DTx development, to date, no single unifying framework guides DTx evidence production and regulatory decision-making [7-11]. By evidence production, we mean the use of scientific methods and processes to produce meaningful data about interventions, such as DTx, both qualitative and quantitative.
J Med Internet Res 2024;26:e49208
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Applications of Clinical Decision Support Systems in Diabetes Care: Scoping Review
According to their decision-making mechanisms, CDSSs are commonly classified into knowledge- or non-knowledge-based systems. The decision-making mechanism of knowledge-based CDSSs is based on explicit, predetermined knowledge rules or guidelines [13], whereas non-knowledge-based CDSSs use artificial intelligence (AI) or machine learning (ML) algorithms to transform large-scale health care data into meaningful information for users to make decisions [12,14].
J Med Internet Res 2023;25:e51024
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Our work is the first large-scale quantitative analysis of referrals to SNFs and associated offer or denial decisions and represents a first step toward providing sequential decision support to personnel managing SNF admissions.
J Med Internet Res 2023;25:e43518
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