Physical activity, patient-reported symptoms, and clinical events: Insights into postprocedural recovery from personal digital devices

Bartlett, Victoria; Ross, Joseph S.; Shah, Nilay D.; Ciaccio, Laura; Akar, Joseph G.; Noseworthy, Peter A.; Dhruva, Sanket S.

doi:10.1016/j.cvdhj.2021.06.002

Cited by 6 publications

(6 citation statements)

References 33 publications

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“…Россия одной из первых стран в мире приступила к разработке квазиметрических стандартов, и уже в текущем году вступят в силу 15 отраслевых стандартов в сфере искусственного интеллекта (из них два -по медицине). Системы искусственного интеллекта (СИИ) применяются всё шире и практически во всех отраслях медицины [2]: это и значительное число работ по оценке электрокардиографии (ЭКГ), в том числе посредством смарт-часов [3][4][5][6][7], и нарастающее количество исследований в области компьютерного зрения по всему миру [8,9] Таким образом, при анализе публичных открытых наборов данных по ЭКГ нами были сформулированы следующие основные проблемы:…”

Section: аннотацияunclassified

“…Россия одной из первых стран в мире стала разрабатывать квазиметрические стандарты. В 2023 году вступят в силу уже 15 отраслевых стандартов в сфере искусственного интеллекта, два из них -по медицине 7,8 .…”

Section: нормативные документы регламентирующие разработку и применен...unclassified

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Artificial intelligence in clinical physiology: How to improve learning agility

Shutov¹,

Sharova²,

Abuladze³

et al. 2023

Digital Diagnostics

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Artificial intelligence is increasingly being used in medicine, including clinical physiology. This is facilitated by the increase in computing processing power, the development of cloud services and datasets, and numerous scientific articles demonstrating the effectiveness and viability of such intelligent solutions. Although the approach to medical datasets development is generally similar, there are a number of key features and significant differences in clinical physiology ones. Artificial intelligence systems in clinical physiology may be effectively trained and applied in practice by following the recommendations proposed in this article.

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Section: аннотацияunclassified

Section: нормативные документы регламентирующие разработку и применен...unclassified

Artificial intelligence in clinical physiology: How to improve learning agility

Shutov¹,

Sharova²,

Abuladze³

et al. 2023

Digital Diagnostics

View full text Add to dashboard Cite

show abstract

“…Perangkat digital pribadi dapat menjadi pilihan informasi pemulihan pasien dan pendekatan pemantauan jarak jauh (telemonitoring) pada pasien AF setelah ablasi kateter (Bartlett et al, 2021). Manajemen pasien jarak jauh (RPM) yang mencangkup intervensi telemonitoring dan telemedis, sebagai kontrol detak dan irama jantung, yang memungkinkan deteksi dini AF pasien HF dan intervensi yang lebih cepat dan peningkatan pemberdayaan pasien (Stegmann et al, 2020).…”

Section: Pendahuluanunclassified

“…Tabel berikut menunjukan rangkuman analisis dari tujuh artikel yang berfokus pada penggunaan mobil health dalam telemonitoring fibrilasi atrium (Bartlett et al, 2021;Choi et al, 2020;Guo et al, 2020;Hermans et al, 2020, Hermans et al, 2022Knaepen et al, 2021;Stegmann et al, 2020). Hasil analisis menunjukan terdapat tiga kelompok penggunaan mobile health dalam telemonitoring fibrilasi atrium, yaitu:…”

Section: Hasilunclassified

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Use of mHealth in Atrial Fibrillation Telemonitoring: A Literature Review

Ningrum,

Herawati

2023

JNC

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Management of atrial fibrillation (AF) is limited to low detection, treatment non-adherence and several other considerations, resulting in the utilization of mobile health devices (mHealth) for comprehensive and continuous telemonitoring of atrial fibrillation. This study aims to identify the use of mHealth in atrial fibriullation telemonitoring. The reseach design is a literature review using the PRISMA method approach. Literature search used the keywords “mHealth” and “telemonitoring” and “atrial fibrillation” from the PubMed, Science Direct, Scopus and ProQuest databases, with inclusion criteria namely article on the use technology or mobile health-based applications in telemonitoring atrial fibrillation (AF), articles less than 5 years, fulltext and open access. The seven articles analyzed, six articles on the use of mHealth can be used for atrial fibrillation telemonitoring and one article shows the use of applications for educational media. Further development is needed in line with increasing needs, ease of use and technological developments in the health sector.

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Systematic development of a patient-reported ONCOlogical-ROUTinE-Screening (ONCO-ROUTES) procedure at the University Cancer Center Regensburg

Maurer,

Saibold,

Gerl

et al. 2024

J Cancer Res Clin Oncol

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Purpose The evaluation of treatment success and progression in oncology patient-reported outcomes (PROs) is playing an increasingly important role. Meanwhile, PROs are a component of the certification requirements of the German Cancer Society for oncology centers. PROs are used to provide supportive therapy. There is currently no instrument that fully covers the requirements. At the University Hospital Regensburg (UKR), a digital ONCOlogical-ROUTinE-Screening (ONCO-ROUTES) procedure was developed in order to assess the need for supportive therapy in a standardized way and to provide patients with supportive interventions tailored to their needs. Methods On the basis of current requirements and guidelines, the development of ONCO-ROUTES was supported by experts in focus groups and interviews, and digitalization was carried out in connection with the IT infrastructure. Results A Needs-based, Quality-of-life (QoL) and Symptoms Screening (NQS2) tool already established in the routine at the UKR was further developed into ONCO-ROUTES, which is made up of the domains therapy phase, nutrition, tobacco use, alcohol use, quality of life, general condition/functional status, physical activity, psychooncology, social services, and further support needs. By linking the digitized questionnaire to the hospital information system, the results are available for immediate use in routine operations and thus for the referral of patients for further supportive therapy. Conclusion The digital PRO application ONCO-ROUTES is designed to involve patients in monitoring additional supportive needs and thus, improves supportive interdisciplinary treatment.

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Physical activity, patient-reported symptoms, and clinical events: Insights into postprocedural recovery from personal digital devices

Cited by 6 publications

References 33 publications

Artificial intelligence in clinical physiology: How to improve learning agility

Artificial intelligence in clinical physiology: How to improve learning agility

Use of mHealth in Atrial Fibrillation Telemonitoring: A Literature Review

Systematic development of a patient-reported ONCOlogical-ROUTinE-Screening (ONCO-ROUTES) procedure at the University Cancer Center Regensburg

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