ArticleScientific reports2021
Personalized treatment options for chronic diseases using precision cohort analytics.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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.
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.
Who cites it
17 citing papers in PubMed.
- Prescribing Trajectories in Type 2 Diabetes in the United States, 2019-2024.Diabetes, obesity & metabolism · 2026Article
- Identification of a personalized eGFR threshold improves the prediction of kidney failure risk after transplantation.Communications medicine · 2026Article
- A platform for generating clinical intelligence from routine health data in hospitals: PICTURE.Future healthcare journal · 2026Article
- Matched tissue-blood whole-exome sequencing improves detection of genetic etiologies in pediatric drug-resistant epilepsy.Frontiers in pediatrics · 2026Article
- Predicting Zygosity based on physical similarity of twin pairs with the aid of machine learning methods.BMC medical informatics and decision making · 2025Article
- Phenotyping Fatigue Profiles in Marfan Syndrome Through Cluster Analysis: A Cross-Sectional Study of Psychosocial and Clinical Correlates.Journal of clinical medicine · 2025Article
- Artificial Intelligence-Driven Strategies for Targeted Delivery and Enhanced Stability of RNA-Based Lipid Nanoparticle Cancer Vaccines.Pharmaceutics · 2025Review
- Strategies to Reduce Hospital Length of Stay: Evidence and Challenges.Medicina (Kaunas, Lithuania) · 2025Review
- Human-centered design of a health recommender system for orthopaedic shoulder treatment.BMC medical informatics and decision making · 2025Article
- Human-centered Design of a Health Recommender System for Orthopaedic Shoulder Treatment.Research square · 2024Article
- Deriving Treatment Decision Support From Dutch Electronic Health Records by Exploring the Applicability of a Precision Cohort-Based Procedure for Patients With Type 2 Diabetes Mellitus: Precision Cohort Study.Online journal of public health informatics · 2024Article
- AI's pivotal impact on redefining stakeholder roles and their interactions in medical education and health care.Frontiers in digital health · 2024Article
- New Horizons in artificial intelligence in the healthcare of older people.Age and ageing · 2023Article
- Construction of Cohorts of Similar Patients From Automatic Extraction of Medical Concepts: Phenotype Extraction Study.JMIR medical informatics · 2022Article
- Diabetes medication recommendation system using patient similarity analytics.Scientific reports · 2022Article
- Enhancing Clinical Prediction Performance by Incorporating Intuition.Journal of medical systems · 2021Article
- Artificial Intelligence in Clinical Diagnosis and Treatment of Dry Eye: Workflows, Effectiveness, and Evaluation.Journal of current ophthalmologyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To support point-of-care decision making by presenting outcomes of past treatment choices for cohorts of similar patients based on observational data from electronic health records (EHRs), a machine-learning precision cohort treatment option (PCTO) workflow consisting of (1) data extraction, (2) similarity model training, (3) precision cohort identification, and (4) treatment options analysis was developed. The similarity model is used to dynamically create a cohort of similar patients, to inform clinical decisions about an individual patient. The workflow was implemented using EHR data from a large health care provider for three different highly prevalent chronic diseases: hypertension (HTN), type 2 diabetes mellitus (T2DM), and hyperlipidemia (HL). A retrospective analysis demonstrated that treatment options with better outcomes were available for a majority of cases (75%, 74%, 85% for HTN, T2DM, HL, respectively). The models for HTN and T2DM were deployed in a pilot study with primary care physicians using it during clinic visits. A novel data-analytic workflow was developed to create patient-similarity models that dynamically generate personalized treatment insights at the point-of-care. By leveraging both knowledge-driven treatment guidelines and data-driven EHR data, physicians can incorporate real-world evidence in their medical decision-making process when considering treatment options for individual patients.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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 OpenQuestion graph.