Smart healthcare: the role of AI, robotics, and NLP in advancing telemedicine and remote patient monitoring

The integration of artificial intelligence (AI), robotics, and natural language processing (NLP) is transforming healthcare delivery through telemedicine and remote patient monitoring (RPM). These technologies are increasingly being adopted to enhance diagnostic accuracy, patient engagement, and healthcare accessibility. This review examines the application of AI, robotics, and NLP across various medical domains including cardiology, diabetes, gynaecology, dermatology, and general RPM. • AI facilitates precise diagnosis, predictive analytics, and personalized medicine. • NLP enables efficient processing of medical records, symptom triage, and virtual health assistance. • Robotics supports minimally invasive surgery, remote interventions, and routine clinical tasks. Case studies highlight successful implementations and measurable outcomes demonstrating improved efficiency and patient outcomes. However, several challenges persist, such as concerns over data privacy, high implementation costs, lack of clinician training, and ethical considerations. Furthermore, integration of these advanced tools into cohesive telemedicine systems remains limited. Regulatory frameworks addressing safety, accountability, and standardization are still in development. Addressing existing technological, ethical, and policy gaps is essential to fully realize the potential of intelligent healthcare systems. Strengthening regulatory standards, ensuring interoperability, and enhancing clinician preparedness will be key to achieving effective, equitable, and safe patient care in the digital era.

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Publication Details

Journal
BMC Artificial Intelligence
Published
2025-11-03
DOI
https://doi.org/10.1186/s44398-025-00015-4
Citations
4
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
2.62
Controls
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article

Smart healthcare: the role of AI, robotics, and NLP in advancing telemedicine and remote patient monitoring

Pooja Sharma
4 citations
BMC Artificial Intelligence
Artificial Intelligence in Healthcare and Education
2.62
article

Smart healthcare: the role of AI, robotics, and NLP in advancing telemedicine and remote patient monitoring

Pooja Sharma
article en
4 citations

Abstract

The integration of artificial intelligence (AI), robotics, and natural language processing (NLP) is transforming healthcare delivery through telemedicine and remote patient monitoring (RPM). These technologies are increasingly being adopted to enhance diagnostic accuracy, patient engagement, and healthcare accessibility. This review examines the application of AI, robotics, and NLP across various medical domains including cardiology, diabetes, gynaecology, dermatology, and general RPM. • AI facilitates precise diagnosis, predictive analytics, and personalized medicine. • NLP enables efficient processing of medical records, symptom triage, and virtual health assistance. • Robotics supports minimally invasive surgery, remote interventions, and routine clinical tasks. Case studies highlight successful implementations and measurable outcomes demonstrating improved efficiency and patient outcomes. However, several challenges persist, such as concerns over data privacy, high implementation costs, lack of clinician training, and ethical considerations. Furthermore, integration of these advanced tools into cohesive telemedicine systems remains limited. Regulatory frameworks addressing safety, accountability, and standardization are still in development. Addressing existing technological, ethical, and policy gaps is essential to fully realize the potential of intelligent healthcare systems. Strengthening regulatory standards, ensuring interoperability, and enhancing clinician preparedness will be key to achieving effective, equitable, and safe patient care in the digital era.

BMC Artificial IntelligenceVol. 1(1)
Punjab Technical University (IN)
Openalex Percentile: Top 8%
Artificial Intelligence in Healthcare and Education
2.62
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