Artificial Intelligence [AI] and Homoeopathy: Applicability, Reliability, Validity and Limitations of an AI-Aided Homoeopathic Clinic

Authors

  • Ashok Vishwambhar Anpat MD (Hom.), PhD (Scholar), Principal & Medical Superintendent, Professor &Head, Department of Homoeopathic Repertory, Sai Homoeopathy Medical College, Hospital, Sasure, Vairag, Solapur (MS), India https://orcid.org/0009-0000-6328-1776
  • Patil Snehal Jayant MD[Hom], Assistant Professor, Dept of Repertory, SHMC, Sasure, Vairag, Solapur
  • Ingale Madhubala Tukaram MD[Hom], Assistant Prof, Dept of Physiology, SHMC, Sasure, Vairag, Solapur
  • Kakade Mayur Haribhahu MD [ Hom], Assistant Prof, Dept of Surgery, SHMC, Sasure, Vairag, Solapur

Abstract

Individualization is the cornerstone of homoeopathic practice; however, the process is highly subjective and varies between practitioners due to differences in observation, interpretation, and analysis of symptoms. Recent advancements in Artificial Intelligence (AI), multimodal data collection, and machine learning offer an unprecedented opportunity to enhance precision in homoeopathic case-taking and remedy selection. This conceptual research proposes an AI-Aided Homoeopathic Clinic model integrating 360° multisensory recording, natural language processing (NLP), emotion-tone analysis, gesture recognition, and a curated digital knowledge base of Materia Medica, Repertory, Organon, and clinical literature. The model aims to reduce human errors, increase reproducibility in remedy selection, and strengthen the validity and reliability of homoeopathic prescribing. The paper explores applicability, reliability, validity, limitations, ethical considerations, and future possibilities of AI in homoeopathic practice. This concept has the potential to become a milestone in homoeopathic clinical methodology, guiding the future of precision homoeopathy.

Keywords: Artificial Intelligence, Homoeopathy, Individualisation, Repertory, Materia Medica, 360° Recording, NLP, Machine Learning, Futuristic Medicine, AI-Aided Homoeopathic Clinic.

Keywords:

Artificial Intelligence, Homoeopathy, Individualisation, Repertory, Materia Medica, 360° Recording, NLP, Machine Learning, Futuristic Medicine, AI-Aided Homoeopathic Clinic

DOI

https://doi.org/10.22270/jddt.v16i1.7505

Author Biographies

Ashok Vishwambhar Anpat , MD (Hom.), PhD (Scholar), Principal & Medical Superintendent, Professor &Head, Department of Homoeopathic Repertory, Sai Homoeopathy Medical College, Hospital, Sasure, Vairag, Solapur (MS), India

MD (Hom.), PhD (Scholar), Principal & Medical Superintendent, Professor &Head, Department of Homoeopathic Repertory, Sai Homoeopathy Medical College, Hospital, Sasure, Vairag, Solapur (MS), India

Patil Snehal Jayant, MD[Hom], Assistant Professor, Dept of Repertory, SHMC, Sasure, Vairag, Solapur

MD[Hom], Assistant Professor, Dept of Repertory, SHMC, Sasure, Vairag, Solapur

Ingale Madhubala Tukaram , MD[Hom], Assistant Prof, Dept of Physiology, SHMC, Sasure, Vairag, Solapur

MD[Hom], Assistant Prof, Dept of Physiology, SHMC, Sasure, Vairag, Solapur

Kakade Mayur Haribhahu, MD [ Hom], Assistant Prof, Dept of Surgery, SHMC, Sasure, Vairag, Solapur

MD [ Hom], Assistant Prof, Dept of Surgery, SHMC, Sasure, Vairag, Solapur

References

1. Hahnemann S. Organon of Medicine, 6th Edition.

2. Kent JT. Lectures on Homoeopathic Philosophy.

3. Boenninghausen C.v. Therapeutic Pocketbook.

4. Boger CM. Synoptic Key of the Materia Medica.

5. Phatak SR. Repertory of Homoeopathic Materia Medica.

6. Recent AI in Health journals (e.g., Lancet Digital Health, Nature Medicine).

Published

2026-01-15
Statistics
Abstract Display: 45
PDF Downloads: 22
PDF Downloads: 6

How to Cite

1.
Anpat AV, Jayant PS, Tukaram IM, Haribhahu KM. Artificial Intelligence [AI] and Homoeopathy: Applicability, Reliability, Validity and Limitations of an AI-Aided Homoeopathic Clinic. J. Drug Delivery Ther. [Internet]. 2026 Jan. 15 [cited 2026 Jan. 19];16(1):143-5. Available from: https://www.jddtonline.info/index.php/jddt/article/view/7505

Issue

Vol. 16 No. 1 (2026): Volume 16, Issue 1, Jan 2026

Section

Review

Copyright (c) 2026 Ashok Vishwambhar Anpat , Patil Snehal Jayant, Ingale Madhubala Tukaram , Kakade Mayur Haribhahu

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Authors who publish with this journal agree to the following terms:

  1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).

How to Cite

1.
Anpat AV, Jayant PS, Tukaram IM, Haribhahu KM. Artificial Intelligence [AI] and Homoeopathy: Applicability, Reliability, Validity and Limitations of an AI-Aided Homoeopathic Clinic. J. Drug Delivery Ther. [Internet]. 2026 Jan. 15 [cited 2026 Jan. 19];16(1):143-5. Available from: https://www.jddtonline.info/index.php/jddt/article/view/7505
Crossref
Scopus
Google Scholar
Europe PMC