Adam M. Chekroud
- Applied Psychology top 1%
- Digital Mental Health Interventions 4
- Health Informatics top 1%
-
- Mental Health Research Topics 12
- Biological Psychiatry top 2%
- Cognitive Neuroscience top 5%
- Functional Brain Connectivity Studies 11
-
- Mental Health Treatment and Access 9
-
- Treatment of Major Depression 8
-
- Workplace Health and Well-being 6
-
- Schizophrenia research and treatment 4
-
- Machine Learning in Healthcare 3
- Co-authors
- John H. KrystalRalitza GueorguievaHarlan M. KrumholzMartin P. PaulusAmanda B. ZheutlinSammi R. ChekroudMadhukar H. TrivediPhilip R. Corlett
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Adam M. Chekroud
34 papers receiving 2.7k citations
Hit Papers
Peers
Comparison fields: 5 of 153
- Applied Psychology 400
- Health Informatics 97
- Experimental and Cognitive Psychology 859
- Biological Psychiatry 158
- Cognitive Neuroscience 629
Countries citing papers authored by Adam M. Chekroud
This map shows the geographic impact of Adam M. Chekroud's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Adam M. Chekroud with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Adam M. Chekroud more than expected).
Fields of papers citing papers by Adam M. Chekroud
This network shows the impact of papers produced by Adam M. Chekroud. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Adam M. Chekroud. The network helps show where Adam M. Chekroud may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Adam M. Chekroud, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2026 | 0 | |
| 2 | 2025 | 2 | |
| 3 | 2025 | 1 | |
| 4 | 2025 | 0 | |
| 5 | 2025 | 0 | |
| 6 | 2025 | 0 | |
| 7 | 2025 | 7 | |
| 8 | Illusory generalizability of clinical prediction modelsbreakdown → | 2024 | 111 |
| 9 | 2023 | 1 | |
| 10 | 2021 | 5 | |
| 11 | 2020 | 42 | |
| 12 | 2020 | 106 | |
| 13 | 2019 | 103 | |
| 14 | 2019 | 16 | |
| 15 | 2018 | 43 | |
| 16 | 2017 | 176 | |
| 17 | 2017 | 48 | |
| 18 | 2017 | 192 | |
| 19 | Cross-trial prediction of treatment outcome in depression: a machine learning approachbreakdown → | 2016 | 452 |
| 20 | 2014 | 55 |
About Adam M. Chekroud
Adam M. Chekroud is a scholar working on Experimental and Cognitive Psychology, Applied Psychology and General Psychology, having authored 38 papers that have together received 2.8k indexed citations. Recurring topics across this work include Mental Health Research Topics (12 papers), Functional Brain Connectivity Studies (11 papers), Mental Health Treatment and Access (9 papers), Treatment of Major Depression (8 papers), Workplace Health and Well-being (6 papers), Digital Mental Health Interventions (4 papers), Schizophrenia research and treatment (4 papers) and Machine Learning in Healthcare (3 papers). The work is most often cited by research in Applied Psychology (400 citations), Health Informatics (97 citations) and Experimental and Cognitive Psychology (859 citations). Adam M. Chekroud has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include John H. Krystal, Ralitza Gueorguieva, Harlan M. Krumholz, Martin P. Paulus, Amanda B. Zheutlin, Sammi R. Chekroud, Madhukar H. Trivedi, Philip R. Corlett, Tyrone D. Cannon and Marcia K. Johnson. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and Neuron.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.