AI and telemedicine in general practice in 2025

Alberto Parada

Keywords: Artificial Intelligence, Telemedicine, General Practice, Personalized Diagnosis, Medical Innovation.

Background:

Artificial Intelligence (AI) and telemedicine are rapidly transforming general practice, offering potential benefits in diagnosis, treatment, and patient care.
These technologies are transforming medical practice by increasing the quality of care and treatment efficiency. However, their specific advantages and challenges in primary care settings are not fully understood.

Research questions:

What are the specific advantages of AI and telemedicine in enhancing diagnostic accuracy, treatment personalization, and healthcare accessibility in general practice?

Method:

This study employs a mixed-methods approach, combining quantitative analysis of diagnostic accuracy and treatment outcomes with qualitative interviews of healthcare professionals. Participants include general practitioners and patients from both urban and rural settings. Data collection involves medical record analysis, AI algorithm performance metrics, and thematic analysis of interview transcripts.

Results:

Preliminary results indicate that AI significantly improves early disease detection, with a 20% increase in diagnostic accuracy for chronic conditions such as diabetes and cancer. Personalized treatment plans generated by AI algorithms show a 15% reduction in adverse effects. Telemedicine enhances healthcare accessibility, with a 30% increase in patient consultations in rural areas. These findings are based on initial data from an ongoing study.

Conclusions:

AI and telemedicine offer substantial benefits in general practice, including improved diagnostics, personalized care, and increased access. However, significant challenges remain in ethics, data security, and integration into clinical workflows.
These findings highlight the need for comprehensive training programs and clear regulatory frameworks to maximize the potential of these technologies while addressing key concerns.
The robustness of these results is supported by the mixed-methods approach and diverse participant sample.

Points for discussion:

Ethical implications and regulatory frameworks for AI in healthcare

Impact of AI and telemedicine on healthcare accessibility and efficiency

Balancing AI integration with the human element in healthcare

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