ReviewJournal of translational medicine2026
Medical software for precision diagnostics of infection with immunoprofiling and artificial intelligence.
Review in Journal of translational medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWhat does it take to realize one-click precision diagnostics across infections? Traditional biomedical methods often are limited to detect a single pathogen at a time, thus neglecting the complex dynamics of the immune response and its degrees of individuality, the host-microbe interactions, and the connection to other disease-states that can significantly affect diagnoses. MAIN BODY: Here we review methods employed in the clinical microbiology laboratory, sequencing and machine learning technologies, that enable precision diagnostics of infectious diseases. We provide a roadmap of the regulatory pathways and touch upon engineering requirements necessary for developing and bringing to market a medical software for physicians and citizens. We anticipate that high-throughput sequencing technologies, together with artificial intelligence, unlock the use of complex information of the immune response at the single-molecule level thus enable the precise diagnosis of multiple infections, the predictions of clinical outcomes based on individual immune baselines, microbial colonization, and therapeutic history.
conclusionsThese methods, combined in a medical software, hold the potential to concomitantly diagnose and predict the clinical course of additional immune-related diseases such as cancer and autoimmunity. Thus, uncovering the immunity-interface to several diseases can have a direct impact on population immunity, One Health, and pandemic preparedness.
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