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आयुर्वेद ज्योतिष

by Lakshmi Narayan Sharma

Ayurvedic and astrological approaches to illness through horoscope case studies

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AlbakiReads Editorial

Ayurvedic and astrological approaches to illness through horoscope case studies

Lakshmi Narayan Sharma presents disease prediction and treatment through a framework that combines astrological calculation with Ayurvedic methods. The book is organized across 25 chapters and relies heavily on horoscopes as worked material: the opening chapters include 14 charts, followed by 83 charts arranged around the twelve houses. Later sections address charts connected with specific illnesses described as incurable and with untimely death. Five additional disease examples incorporate Navansh, Dreshkan, Dwadshansh, and Trishansh kundlis. The emphasis is on using these chart forms to assess the stated condition of illness within the book’s astrological-Ayurvedic system.

Good fit for readers who enjoy

  • Readers interested in Jyotish applications related to health and disease
  • Students of Ayurvedic and astrological interpretive methods
  • Those seeking a chart-based reference with numerous horoscope examples

Themes

AyurvedaMedical astrologyHoroscope interpretationDisease predictionKundli analysis

Based on publisher information and book metadata.

Book overview

In today's fast-paced life, every person is suffering from some disease or the other. key reason for this is the new lifestyle and the changing food habits. Prediction and treatment of diseases is possible through astrological calculations and ayurvedic methods. The presented book 'Ayurveda Jyotish' has 25 chapters. There are 14 horoscopes in the first 9 chapters, 83 horoscopes of twelve houses (in Chapter 10 to Chapter 21), 7 horoscopes of specific incurable diseases in 'Chapter 22' and 20 horoscopes of untimely death in 'Chapter 23'. Five example horoscopes of diseases, along with Navansh Kundli, Dreshkan Kundli, Dwadshansh Kundli and Trishansh Kundli, are also given. With their help the condition of any disease can be predicted.

 

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