Healing at a Distance: Telemedicine and Remote Care in the Age of Artificial Intelligence
Bibliographic record
Abstract
Rachmad, Yoesoep Edhie. 2021. Healing at a Distance: Telemedicine and Remote Care in the Age of Artificial Intelligence. Book of Medical Internet Research; Toronto Special Issue, 2021. https://doi.org/10.17605/osf.io/vghr3 "Healing at a Distance: Telemedicine and Remote Care in the Age of Artificial Intelligence" by Yoesoep Edhie Rachmad, published in 2021 by the Book of Medical Internet Research in Toronto, explores the transformative impact of telemedicine and AI on healthcare delivery. The book addresses the increasing need for accessible and high-quality healthcare solutions, especially in remote and underserved areas. It provides a comprehensive overview of how telemedicine has evolved and the pivotal role AI plays in enhancing remote care. Definition and Basic Concepts The book begins with an introduction to telemedicine and remote care, defining these concepts and tracing their development over the years. Telemedicine refers to the use of telecommunication technology to provide healthcare services from a distance, while remote care encompasses a broader spectrum of health services delivered outside traditional healthcare settings. AI is presented as a key enabler, enhancing the capabilities of telemedicine through advanced algorithms and data analysis. Underlying Phenomena The motivation for this book stems from the rapid advancements in telecommunication and AI technologies, coupled with the growing demand for healthcare accessibility. The COVID-19 pandemic has further accelerated the adoption of telemedicine, highlighting its importance in ensuring continuity of care. The book emphasizes how these technological advancements can address critical healthcare challenges and improve patient outcomes. Problem Statement The central problem addressed by the book is the integration of AI into telemedicine and remote care. It examines the challenges and opportunities of incorporating AI technologies in telemedicine, aiming to understand how these technologies can be effectively utilized to expand access, improve quality, and ensure sustainability of healthcare services. Research Objectives The book aims to explore the various applications of AI in telemedicine, providing a comprehensive analysis of their benefits, challenges, and future potential. It seeks to offer insights into how these technologies can be implemented to enhance remote care, emphasizing the importance of ethical guidelines and regulatory frameworks to ensure responsible use. Indicators Key indicators of successful AI integration in telemedicine, as identified in the book, include improved patient triage, accurate initial diagnoses, efficient case management, and enhanced patient engagement. The book also highlights the importance of robust technological infrastructure and supportive regulatory policies as critical indicators. Operational Variables Operational variables discussed in the book include AI technologies such as machine learning algorithms, natural language processing tools, and IoT devices. The book also explores variables related to patient outcomes, data management practices, and regulatory compliance. Determining Factors Several factors are crucial for the successful implementation of AI in telemedicine, including technological advancements, healthcare professionals' readiness to adopt new tools, regulatory support, and patient acceptance. The author emphasizes the role of interdisciplinary collaboration and continuous innovation in overcoming technical and ethical challenges. Implementation and Strategy The book outlines various strategies for integrating AI into telemedicine, such as investing in AI research and development, fostering collaboration between technology developers and healthcare providers, and establishing comprehensive training programs for healthcare workers. It also highlights the need for continuous monitoring and evaluation to adapt to evolving technologies and healthcare needs. Challenges and Supportive Factors The book identifies several challenges, including data privacy concerns, algorithmic biases, and the complexity of cross-jurisdictional medical licensing. Supportive factors include ongoing technological innovations, supportive regulatory policies, and positive patient outcomes. The author calls for a balanced approach to address these challenges while leveraging supportive factors to maximize the benefits of AI in telemedicine. Determining Factors of the Book The relevance and impact of the book are determined by its timely exploration of emerging technologies, its comprehensive analysis, and its practical recommendations for healthcare professionals and policymakers. The book’s ability to address ethical considerations and propose actionable strategies also contributes significantly to its importance. Research Findings The book presents several case studies demonstrating successful applications of telemedicine and AI in various healthcare settings. These include efficient patient triage systems, remote diagnostic tools, and effective chronic disease management programs. These findings illustrate the tangible benefits of AI integration, providing evidence of its potential to transform remote healthcare delivery. Conclusion and Recommendations In conclusion, the book emphasizes the vital role of telemedicine and AI in modernizing healthcare. It advocates for the ethical and responsible adoption of these technologies, emphasizing the need for regulatory frameworks and continuous evaluation. The author recommends fostering interdisciplinary collaborations, investing in technological innovations, and developing comprehensive regulatory frameworks to ensure the successful integration of AI in telemedicine. "Healing at a Distance: Telemedicine and Remote Care in the Age of AI" offers a detailed exploration of how telemedicine and AI can overcome geographical and resource barriers, enhancing the quality and effectiveness of healthcare. It underscores the importance of innovation, ethical responsibility, and strategic implementation to harness the full potential of these transformative technologies. Buku: "Healing at a Distance: Telemedicine and Remote Care in the Age of AI" Bab 1: Pengantar ke Telemedisin dan Perawatan Jarak Jauh • Isi: Bab ini memberikan gambaran umum tentang evolusi telemedisin dan perawatan jarak jauh, menyoroti bagaimana teknologi, terutama AI, telah memungkinkan perkembangan pesat dalam bidang ini. • Kesimpulan: Telemedisin telah berkembang menjadi solusi kesehatan kritis yang memperluas akses dan meningkatkan kualitas perawatan, terutama di area terpencil. Bab 2: AI dalam Telemedisin • Isi: Menganalisis peran AI dalam meningkatkan layanan telemedisin melalui algoritma yang dapat melakukan triase pasien, diagnosa awal, dan manajemen kasus. • Kesimpulan: Penggunaan AI dalam telemedisin menawarkan potensi untuk membuat layanan kesehatan lebih efisien dan dapat diakses oleh lebih banyak orang. Bab 3: Teknologi Pendukung Telemedisin • Isi: Mendiskusikan berbagai teknologi yang mendukung telemedisin, termasuk platform komunikasi, perangkat IoT kesehatan, dan sistem manajemen data. • Kesimpulan: Infrastruktur teknologi yang solid adalah kunci untuk menyediakan layanan telemedisin yang aman, efektif, dan berkelanjutan. Bab 4: Pengaruh Telemedisin pada Perawatan Primer • Isi: Mengeksplorasi dampak telemedisin pada perawatan primer, bagaimana itu mengubah interaksi dokter-pasien dan pengelolaan penyakit kronis. • Kesimpulan: Telemedisin telah menjadi alat penting dalam perawatan primer, meningkatkan monitoring terus-menerus dan pendekatan perawatan preventif. Bab 5: Isu Hukum dan Regulasi • Isi: Membahas tantangan hukum dan regulasi yang dihadapi oleh penyedia telemedisin, termasuk privasi data, keamanan, dan lintas yurisdiksi perizinan medis. • Kesimpulan: Memahami dan mengatasi tantangan regulasi adalah esensial untuk integrasi yang sukses dan etis dari telemedisin dalam sistem kesehatan. Bab 6: Studi Kasus Global • Isi: Menampilkan berbagai studi kasus dari seluruh dunia yang menunjukkan penerapan efektif dan inovatif dari telemedisin dan perawatan jarak jauh. • Kesimpulan: Studi kasus ini menyoroti keberhasilan dan tantangan telemedisin, memberikan wawasan penting untuk pengembangan masa depan. Bab 7: Masa Depan Telemedisin • Isi: Meninjau perkiraan masa depan telemedisin, termasuk peran potensial teknologi baru seperti AI lanjutan, realitas virtual, dan lebih lagi. • Kesimpulan: Masa depan telemedisin dipenuhi dengan peluang untuk inovasi lebih lanjut yang akan terus mengubah cara layanan kesehatan disediakan. Kesimpulan Akhir: • Isi: Bab ini mengintegrasikan semua poin kunci dari bab-bab sebelumnya, menegaskan kembali pentingnya telemedisin dalam masyarakat modern dan bagaimana AI berpotensi memperluas kemampuannya. • Kesimpulan: Seiring berkembangnya teknologi, telemedisin akan terus memainkan peran penting dalam menyediakan akses perawatan kesehatan yang inklusif dan berkelanjutan. Buku ini menyediakan pandangan mendalam dan terperinci tentang bagaimana telemedisin dan AI mengubah wajah perawatan kesehatan, mengatasi hambatan geografis dan sumber daya, serta meningkatkan kualitas dan efektivitas perawatan.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.023 | 0.009 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".