e.g. mhealth
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Summary of articles included in this comprehensive review of artificial intelligence in patch testing.
a Genetic Algo Rithm for biomarker selection in high-dimensional Omics with RF-based classifier.
b Tuning set refers to a subset of data used to fine-tune the parameters of a machine learning model. In this study, the tuning set was used to optimize the hyperparameters of RF and LR models before final evaluation on the validation dataset.
JMIR Dermatol 2025;8:e67154
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The outcome of this fine-tuning process is a model that provides a high level of sensitivity and specificity in classifying and differentiating various types of randomized trial publications.
In our study, we initially established a baseline model for classifying publications using traditional machine learning and word embedding techniques to demonstrate the effectiveness of employing a transformer-based model in identifying publications based on nested designs.
JMIR Med Inform 2025;13:e63267
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The Prediction Model Risk of Bias Assessment Tool (PROBAST) was used to evaluate the risk of bias and applicability of all included studies [8]. PROBAST assesses risk of bias across 4 domains: study participants, predictors, outcomes, and statistical analysis, while applicability is evaluated through the first 3 domains.
JMIR Med Inform 2025;13:e64963
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transformer-empowered healthcare conversations: current trends, challenges, and future directions in large language model-enabledmodel
JMIR Dermatol 2025;8:e67551
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Clearly, significant challenges exist even before introducing the added complexities of multicenter studies, which involve substantial clustering (eg, across multiple centers, regions, or countries) and require more rigorous design, analysis, and reporting methods compared to standard prediction model studies [50].
J Med Internet Res 2025;27:e60148
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The model showed significant bias in SCC classification, frequently misclassifying SCC as BCC with a high rate of false-positive results. This aligns with previous research that observed SCC is often mistaken for BCC, particularly when features like pigmentation or rolled borders overlap [8]. Chat GPT’s performance worsened in Prompt 2, where SCC was frequently misclassified as AK.
JMIR Dermatol 2025;8:e67299
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Chat GPT, the large language model (LLM) chatbot, developed by Open AI [4], that started the AI boom in November 2022, became the most popular AI tool of 2023, accounting for over 60.2% of visits between September 2022 and August 2023, with a total of 14.6 billion website visits [5].
JMIR Med Educ 2025;11:e65108
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A 2-stage base model (random forest at both stages) was developed for the initial therapy using patient data, laboratory data, and clinical data. Subsequently, the model was optimized using a variety of parameters, including the number of decision trees and tree depth (the model specifications and results will be published separately once the AI-based CDSS model has been finalized).
JMIR Hum Factors 2025;12:e66699
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