ReviewCardiac failure review2020
Telemedicine, Artificial Intelligence and Humanisation of Clinical Pathways in Heart Failure Management: Back to the Future and Beyond.
Review in Cardiac failure review, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- Heart failure with preserved ejection fraction, from pathophysiology to technology tools aim improve patients' management.Heart failure reviews · 2025Review
- Assessment of IPD Patients' Knowledge and Attitudes Toward Telemedicine at Tertiary Care Hospital of Metro City.Journal of pharmacy & bioallied sciences · 2025Article
- Study design and rationale of the AZIMUTH trial: a smartphone, app-based, E-health-integrated model of care for heart failure patients.European heart journal. Digital health · 2025Article
- AI-assisted heart failure management: A review of clinical applications, case studies, and future directions.Global cardiology science & practice · 2025Review
- Accuracy and safety of an autonomous artificial intelligence clinical assistant conducting telemedicine follow-up assessment for cataract surgery.EClinicalMedicine · 2024Article
- Heart Failure Management through Telehealth: Expanding Care and Connecting Hearts.Journal of clinical medicine · 2024Review
- An Era of Digital Healthcare-A Comprehensive Review of Sensor Technologies and Telehealth Advancements in Chronic Heart Failure Management.Sensors (Basel, Switzerland) · 2024Review
- Telemedicine: an Effective and Low-Cost Lesson From the COVID-19 Pandemic for the Management of Heart Failure Patients.Current heart failure reports · 2023Review
- A 3-Year Single Center Experience With Left Atrial Pressure Remote Monitoring: The Long and Winding Road.Frontiers in cardiovascular medicine · 2022Article
- The Future of Telemedicine in the Management of Heart Failure Patients.Cardiac failure review · 2021Review
- Coronavirus Disease 2019 and Heart Failure: A Multiparametric Approach.Cardiac failure review · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
New technologies have been recently introduced to improve the monitoring of patients with chronic syndromes such as heart failure. Devices can now be employed to gather large amounts of data and data processing through artificial intelligence techniques may improve heart failure management and reduce costs. The analysis of large datasets using an artificial intelligence technique is leading to a paradigm shift in the era of precision medicine. However, the assessment of clinical safety and the evaluation of the potential benefits is still a matter of debate. In this article, the authors aim to focus on the development of these new tools and to draw the attention to their transition in daily clinical practice.
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.