Towards Intelligent Healthcare: Integrating AI for Pill Detection, Symptom Analysis, and Pharmacy Routing

The integration of artificial intelligence (AI) into healthcare systems offers transformative potential, enabling enhanced patient care and operational efficiency. This paper presents a comprehensive AI-powered healthcare solution focusing on three core functionalities: pill identification, symptom-based consultations, and medical navigation. The pill identification module levennbn rages advanced image recognition algorithms to accurately classify medications, reducing the risks of incorrect drug administration. The symptom-based consultation system employs natural language processing (NLP) and machine learningmodels to provide personalized medical advice by analyzing patient-reported symptoms and crossreferencing medical databases. Lastly, the medical navigation tool assists users in efficiently locating nearby healthcare facilities, specialists, and pharmacies, ensuring timely access to critical services. This AI-driven approach streamlines healthcare delivery, improves diagnostic accuracy, and empowers patients with accessible, on-demand medical assistance.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-08
DOI
https://doi.org/10.5281/zenodo.15361869
Primary Topic
Machine Learning in Healthcare
Type
article
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article

Towards Intelligent Healthcare: Integrating AI for Pill Detection, Symptom Analysis, and Pharmacy Routing

Zenodo (CERN European Organization for Nuclear Research)
Machine Learning in Healthcare
article

Towards Intelligent Healthcare: Integrating AI for Pill Detection, Symptom Analysis, and Pharmacy Routing

article en

Abstract

The integration of artificial intelligence (AI) into healthcare systems offers transformative potential, enabling enhanced patient care and operational efficiency. This paper presents a comprehensive AI-powered healthcare solution focusing on three core functionalities: pill identification, symptom-based consultations, and medical navigation. The pill identification module levennbn rages advanced image recognition algorithms to accurately classify medications, reducing the risks of incorrect drug administration. The symptom-based consultation system employs natural language processing (NLP) and machine learningmodels to provide personalized medical advice by analyzing patient-reported symptoms and crossreferencing medical databases. Lastly, the medical navigation tool assists users in efficiently locating nearby healthcare facilities, specialists, and pharmacies, ensuring timely access to critical services. This AI-driven approach streamlines healthcare delivery, improves diagnostic accuracy, and empowers patients with accessible, on-demand medical assistance.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 75%
Machine Learning in Healthcare
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Towards Intelligent Healthcare: Integrating AI for Pill Detection, Symptom Analysis, and Pharmacy Routing · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS