Mediscan: Doctor Handwriting Recognition with Prescription Summarization, Disease Detection, Drug Insights, and Smart Reminders

Abstract Poor handwriting of medical prescriptions is a significant contributor to the occurrence of medication errors since medical prescriptions are read by hand and thus there is poor legibility. In this paper, I am going to introduce you to MediScan, which is a smart medical helper device, one that combines the handwriting recognition, prescription summary, disease diagnosis, drug analysis, and smart reminder services into one platform. The system uses Optical Character Recognition (OCR) to scan the text on images of a handwritten prescription and a large language model to summarize the context of diagnosis, medications and dosage instructions. According to extracted clinical data, the system detects possible illnesses and conducts drug interaction analysis to increase medication safety. There is also the emergency risk assessment module which notifies the health care providers in case of emergencies and a smart reminder module which reminds the patients to take their medication by sending automatic alerts. The suggested system has a great potential in minimizing the medical interpretation error rates, enhancing patient safety, and providing real-time decision support to clinicians and patients. The system processes text and disease identification correctly, and the analysis of drug compatibility effectively, as experimental assessment demonstrates the effectiveness of the system in practice in healthcare settings.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-04-13
DOI
https://doi.org/10.5281/zenodo.19548154
Primary Topic
Handwritten Text Recognition Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Mediscan: Doctor Handwriting Recognition with Prescription Summarization, Disease Detection, Drug Insights, and Smart Reminders

S. Sanjay, K. Ashokkumar, G Sanjay Kumar
Zenodo (CERN European Organization for Nuclear Research)
Handwritten Text Recognition Techniques
article

Mediscan: Doctor Handwriting Recognition with Prescription Summarization, Disease Detection, Drug Insights, and Smart Reminders

S. Sanjay, K. Ashokkumar, G Sanjay Kumar
article en

Abstract

Abstract Poor handwriting of medical prescriptions is a significant contributor to the occurrence of medication errors since medical prescriptions are read by hand and thus there is poor legibility. In this paper, I am going to introduce you to MediScan, which is a smart medical helper device, one that combines the handwriting recognition, prescription summary, disease diagnosis, drug analysis, and smart reminder services into one platform. The system uses Optical Character Recognition (OCR) to scan the text on images of a handwritten prescription and a large language model to summarize the context of diagnosis, medications and dosage instructions. According to extracted clinical data, the system detects possible illnesses and conducts drug interaction analysis to increase medication safety. There is also the emergency risk assessment module which notifies the health care providers in case of emergencies and a smart reminder module which reminds the patients to take their medication by sending automatic alerts. The suggested system has a great potential in minimizing the medical interpretation error rates, enhancing patient safety, and providing real-time decision support to clinicians and patients. The system processes text and disease identification correctly, and the analysis of drug compatibility effectively, as experimental assessment demonstrates the effectiveness of the system in practice in healthcare settings.

Zenodo (CERN European Organization for Nuclear Research)
Sathyabama Institute of Science and Technology (IN)
Openalex Percentile: Top 7%
Handwritten Text Recognition Techniques
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