Automated Prediction System for Various Health Conditions by Mounts in the Palm

Authors

  • D. Vigneswar Rao  M-Tech, Assistant Professor, Department of CSE, CMR Institute of Technology, Hyderabad, India

Keywords:

Back propagation Neural Network, Digital Image Processing Technique, DDS, Medical Palmistry, Nail Color and Diseases, Palm Textures, Skin Type

Abstract

As of late, palm print recognizable proof innovation has been generally completed and utilized as a part of fields, for example, character acknowledgment. In the meantime, a few highlights of palm and skin strikingly uncover data about infections and wellbeing state of the human body. We can explore the use of palm finding in conventional Chinese medication with the assistance of advanced picture handling innovation. In the field of restorative science, specialists watch nails and palm of patient to get help with analysis of the ailment. Likewise human eyes have a few constraints if there should arise an occurrence of moment perceptions. A branch of palmistry, known as restorative palmistry is one branch where logical investigation of human palm and skin is done to distinguish or foresee the ailments. It has been discovered that today PCs are utilized as a part of human services area for capacity reason yet not for taking choice in regards to finding or forecast of illnesses, i.e. the specialists, who can anticipate or recognize the infection by watching shade of nails and palms, don't have support of PC framework. To connect this hole, the model of choice emotionally supportive network for social insurance in view of restorative palmistry utilizing the methods of advanced picture preparing and investigation is composed and executed to distinguish or anticipate the ailment.

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Published

2018-02-28

Issue

Section

Research Articles

How to Cite

[1]
D. Vigneswar Rao, " Automated Prediction System for Various Health Conditions by Mounts in the Palm, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 1, pp.884-886, January-February-2018.