Machine learning and its applications
in homeopathy research and prescribing

Similia Vol 37 No 2 – December 2024

Author: Sarah Penrose

Abstract

Deep Learning (DL), a subfield of machine learning, is a sophisticated and powerful computer-based tool with superior detection and classification  abilities in complex microscopic image analysis (Xinget al. 2018). When implemented by researchers in the field of homeopathy, DL reveals intricacies  that elude classical analytics. For example, nanoscale pattern differences exist between ‘succussed under turbulence’ or ‘vortex-mixed succussed’ ultra-high dilutions. The DL models used to obtain these patterns, then demonstrated their versatility by evaluating, cataloguing and distinguishing pattern  families (Kokornaczyk et al. 2024, Acuña et al. 2022, 2023). DL also allows for previously unimagined analysis of ultra-high dilutions which, as part of a  suite of analytical techniques, can characterise and differentiate homeopathic remedies by the nature of their initial physical substances and their level of potentisation (Berghian-Grosan et al. 2024).

Keywords: Artificial intelligence, deep learning, machine learning, homeopathy.

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