Psychic Tendency in Artificial Intelligence to Predict Human Psychological Healthcare Crisis
Abstract
As we see in today’s era psychic tendency of
general peoples is weakening some of the reasons behind it is that the Natural
disaster by which we affected recently in 2 years which has created an severe
healthcare nuisance amongst world, similarly working in closed environment
without being dissolved into our colleagues, friends emotions, these are some
things which are constantly resulting in some of the severe human health
problems like Anxiety, Depression, Suicidal thoughts, Bipolar manic disorders
etc. In USA it is reported that the 47000 youngsters of America are under
danger each year through psychological health problems. It is the 10th largest
healthcare problem in United States. As we see from 1930 to 1950 when the base
of actual human machine correlation established by Georges Artsrouni and Peter
Troyanski till date the accuracy between the human emotions and the Computer
machine has not been positively increased and somehow still has problems. In
this Conceptual theory on psychic tendency in natural language programming and
artificial intelligence to predict human psychological problems we have
encouraged some of the problems regarding this manner to be solved which should
help solve this Human psychological healthcare crisis.
Country : India
1 Dr. I. Selvamani
Professor, Department of Electronics and Communication Engineering, Malla Reddy College of Engineering for Women, Hyderabad -500100, Telangana, India
Castro-Sierra
E, Chico PLF, Portugal RA. Neurotransmitters of the limbic system. Amygdala. I.
Part one.. Salud Mental. 2005;28(6):27-32.
Guex, R., Méndez-Bértolo,
C., Moratti, S. et al. Temporal dynamics of amygdala response to emotion- and
action-relevance. SciRep 10, 11138(2020).
Salzman, C.
Daniel. "Amygdala". Encyclopedia Britannica, 27 Feb. 2019,
https://www.britannica.com/science/amygdala. Accessed 6 June 2021.
Marsman A,
Boer VO, Luijten PR, Hulshoff Pol HE, Klomp DWJ, Mandl RCW. Detection of
Glutamate Alterations in the Human Brain Using 1H-MRS: Comparison of STEAM and
sLASER at 7 T. Front Psychiatry. 2017;8:60. Published 2017 Apr 21. doi:10.3389/fpsyt.2017.00060
G. Ranade,
M. Patel and A. Magare, "Emotion Model for Artificial Intelligence and
their Applications," 2018 Fifth International Conference on Parallel,
Distributed and Grid Computing (PDGC), 2018, pp. 335-339, doi:
10.1109/PDGC.2018.8745840.
M. Healy,
R. Donovan, P. Walsh and H. Zheng, "A Machine Learning Emotion Detection
Platform to Support Affective Well Being," 2018 IEEE International
Conference on Bioinformatics and Biomedicine (BIBM), 2018, pp. 2694-2700, doi:
10.1109/BIBM.2018.8621562.
J. G.
Rázuri, D. Sundgren, R. Rahmani and A. M. Cardenas, "Automatic Emotion
Recognition through Facial Expression Analysis in Merged Images Based on an
Artificial Neural Network," 2013 12th Mexican International Conference on
Artificial Intelligence, 2013, pp. 85-96, doi: 10.1109/MICAI.2013.16.
R. Pathar,
A. Adivarekar, A. Mishra and A. Deshmukh, "Human Emotion Recognition using
Convolutional Neural Network in Real Time," 2019 1st International
Conference on Innovations in Information and Communication Technology (ICIICT),
2019, pp. 1-7, doi: 10.1109/ICIICT1.2019.8741491.
