2022
DOI: 10.4018/978-1-7998-8786-7.ch005
|View full text |Cite
|
Sign up to set email alerts
|

Augmenting Mental Healthcare With Artificial Intelligence, Machine Learning, and Challenges in Telemedicine

Abstract: Artificial intelligence is a huge part of the healthcare industry, having applications and uses in oncology, cardiology, dermatology, and many other fields. Another area where AI is constantly attempting to improve is mental healthcare by integrating machine learning to evaluate data generated by mobile and IoT devices. AI aids in the diagnosis and tailoring of therapy for mentally ill individuals at various stages. The artificial intelligence and machine learning methods utilize electronic health records, moo… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
4
1
1

Relationship

0
6

Authors

Journals

citations
Cited by 10 publications
(2 citation statements)
references
References 43 publications
0
2
0
Order By: Relevance
“…Although both the Artificial Intelligence (AI) and machine learning have created new opportunities in the medicine, as a science, designing such precise systems is not easy. Machine Learning is a branch of AI, in which samples are determined which are able to learn and predict available data [ 2 ]. Certainly, robotics is a successful application of machine learning, which can be useful to automatic robot control system with the capability of learning during telesurgery.…”
Section: Dear Editormentioning
confidence: 99%
“…Although both the Artificial Intelligence (AI) and machine learning have created new opportunities in the medicine, as a science, designing such precise systems is not easy. Machine Learning is a branch of AI, in which samples are determined which are able to learn and predict available data [ 2 ]. Certainly, robotics is a successful application of machine learning, which can be useful to automatic robot control system with the capability of learning during telesurgery.…”
Section: Dear Editormentioning
confidence: 99%
“…In addition, disparity in students' family, economic and cultural backgrounds also affect their regularity of attendance in classes. The debarring of students from appearing for the end-term examination that too due to inadequate class attendance leads to serious consequences upon students, ranging from loss of academic progress, dissatisfaction among students, loss of interest towards career, and personal side-effects (Avasthi et al, 2022) such as loss of selfconfidence, self-esteem, mental stress, anxiety, etc.…”
Section: Introductionmentioning
confidence: 99%