Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
2 · The registry
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what money
Authors and funding
14 authors.
Sriya MantenaDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Anders JohnsonDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA.ORCID 0000-0002-1812-9553
Marily OppezzoDepartment of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, CA, 94305, USA.ORCID 0000-0001-6668-2508
Narayan SchuetzDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA.ORCID 0000-0001-5069-407X
Alexander TolasDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA.ORCID 0009-0004-2034-0595
Ritu DoijadDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA.
C Mikael MattsonDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA.ORCID 0000-0002-0642-4838
Allan LawrieNational Heart and Lung Institute, Imperial College London, London, UK.ORCID 0000-0003-4192-9505
Mariana Ramirez-PosadaDepartment of Dermatology, Stanford University School of Medicine, Stanford, CA, 94305, USA.ORCID 0009-0008-9628-3610
Eleni LinosDepartment of Dermatology, Stanford University School of Medicine, Stanford, CA, 94305, USA.ORCID 0000-0002-5856-6301
Abby C KingDepartment of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, CA, 94305, USA.ORCID 0000-0002-7949-8811
Fatima RodriguezDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA.ORCID 0000-0002-5226-0723
Daniel Seung KimDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA.ORCID 0000-0003-2971-1909
Euan A AshleyDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA.ORCID 0000-0001-9418-9577
Funding
CTSA K12 Program at StanfordK12TR004930 · NCATS · STANFORD UNIVERSITY · PI STEVEN M. ASCH, Eleni Linos · 2024 to 2026
$4.2M
Auracle: An AI-Enabled Telecare System to Support the Independence and Safety of Individuals with AD/ADRD and Other DementiasR44AG071211 · NIA · GEN-9, INC. · PI FAUCI, MARK A · 2021 to 2023
$2.9M
Opportunistic Atherosclerotic Cardiovascular Disease Risk Estimation at Abdominal CTs with Robust and Unbiased Deep LearningR01HL167974 · NHLBI · STANFORD UNIVERSITY · PI Imon Banerjee, Akshay Chaudhari · 2023 to 2026
$2.4M
Novel Incidental Calcium Evaluation (NICE)R01HL169345 · NHLBI · STANFORD UNIVERSITY · PI Imon Banerjee, Akshay Chaudhari · 2024 to 2026
$2.1M
Adherence Determinants in the Health Electronic Record Evaluation of Statins (ADHERES)R01HL168188 · NHLBI · STANFORD UNIVERSITY · PI Fatima Rodriguez · 2024 to 2026
$2.1M
Patient Oriented Research in Vulnerable Populations with Skin DiseaseK24AR075060 · NIAMS · STANFORD UNIVERSITY · PI Eleni Linos · 2019 to 2026
$1.6M
Novel digital tools for home-based monitoring of skin diseaseR01AR082109 · NIAMS · STANFORD UNIVERSITY · PI Eleni Linos · 2023 to 2026
Personalized, smartphone-based coaching improves physical activity but relies on static, human-crafted messages. We introduce My Heart Counts (MHC)-Coach, a large language model fine-tuned on the Transtheoretical Model of Change. MHC-Coach generates messages tailored to an individual's psychology (their "stage of change"), providing personalized support to foster long-term physical activity behavior change. To evaluate MHC-Coach's efficacy, 632 participants compared human-expert and MHC-Coach text-based interventions encouraging physical activity. Among messages matched to an individual's stage of change, 68.0% (N=430) preferred MHC-Coach-generated messages (
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.