Abhishek Pratap
Biographic Data
| ID | 7972367 |
|---|---|
| NAME | Abhishek Pratap |
| GIVEN NAMES | Abhishek |
| FAMILY NAME | Pratap |
| SIGNATURE | PRATAP A |
| AFFILIATIONS | Centre for Addiction and Mental Health |
| ORCID | 0000-0002-5289-6932 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2017 |
| LATEST PUBLICATION YEAR | 2021 |
| H-INDEX | 0 |
Artificial Intelligence
Artificial intelligence (AI) in healthcare aims to learn patterns in large multimodal datasets within and across individuals. These patterns may either improve understanding of current clinical status or predict a future outcome. AI holds the potential to revolutionize geriatric mental health care and research by supporting diagnosis, treatment, and clinical decision-making. However, much of this momentum is driven by data and computer scientists…
The efficacy of smartphone‐based mental health interventions for depressive symptoms
The rapid advances and adoption of smartphone technology presents a novel opportunity for delivering mental health interventions on a population scale. Despite multi‐sector investment along with wide‐scale advertising and availability to the general population, the evidence supporting the use of smartphone apps in the treatment of depression has not been empirically evaluated. Thus, we conducted the first meta‐analysis of smartphone apps for depr…
No prominent works on this page.
The efficacy of smartphone‐based mental health interventions for depressive symptoms
The rapid advances and adoption of smartphone technology presents a novel opportunity for delivering mental health interventions on a population scale. Despite multi‐sector investment along with wide‐scale advertising and availability to the general population, the evidence supporting the use of smartphone apps in the treatment of depression has not been empirically evaluated. Thus, we conducted the first meta‐analysis of smartphone apps for depr…
Artificial Intelligence
Artificial intelligence (AI) in healthcare aims to learn patterns in large multimodal datasets within and across individuals. These patterns may either improve understanding of current clinical status or predict a future outcome. AI holds the potential to revolutionize geriatric mental health care and research by supporting diagnosis, treatment, and clinical decision-making. However, much of this momentum is driven by data and computer scientists…
Medicine (2 works) · Mental health (2 works) · Psychiatry (2 works) · Psychology (2 works) · Affect (linguistics) (1 work) · Artificial Intelligence (1 work) · Artificial Intelligence in Healthcare and Education (1 work) · Clinical Practice (1 work) · Clinical Psychology (1 work) · Cognitive behavioral therapy (1 work)