Albert Buchard

7 papers receiving 477 citations

Albert Buchard's Hit Papers

Machine learning for clinical decision support in infectious diseases: a narrative review of current applications 2019 · 354 citations
3540+2+4Years since publication100200300

Peers

Albert Buchard
Comparison fields: 5 of 92
  • Health Informatics 40
  • Applied Microbiology and Biotechnology 29
  • Health Information Management 36
  • Family Practice 9
  • Psychiatry and Mental health 69
Replace Conor K. Corbin with:
Conor K. Corbin United States
Gina Barnes United States
Jeffrey P. Ferraro United States
Marshall Nichols United States
Rosy Tsopra France
Brian R. Jackson United States
Shannan N. Rich United States
Andrew P. Michelson United States
Muhammad Saqib Pakistan
Polina Kukhareva United States
Albert Buchard relative to Conor K. Corbin United States Conor K. Corbin's profile →
Citations per field
00.5×10×17.3×
Conor K. Corbin · 1×
Citations per year

Countries citing papers authored by Albert Buchard

Since Specialization
Citations

This map shows the geographic impact of Albert Buchard'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 Albert Buchard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Albert Buchard more than expected).

Fields of papers citing papers by Albert Buchard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Albert Buchard. 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 Albert Buchard. The network helps show where Albert Buchard may publish in the future.

Co-authors

The 25 scholars most cited alongside Albert Buchard, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Albert Buchard Line = papers co-authored together Albert Buchard links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown
#Work
1
Machine learning for clinical decision support in infectious diseases: a narrative review of current applications
Hit paper breakdown →
2019354
2 201751
3 201833
4 202128
5 202010
6 20248
7 20234
8 20201

About Albert Buchard

Albert Buchard is a scholar working on Social Psychology, Sociology and Political Science, Psychiatry and Mental health, Education and Infectious Diseases, having authored 8 papers that have together received 489 indexed citations. Recurring topics across this work include Psychosomatic Disorders and Their Treatments (2 papers), Child Development and Digital Technology (2 papers), Impact of Technology on Adolescents (2 papers), Grit, Self-Efficacy, and Motivation (2 papers), SARS-CoV-2 and COVID-19 Research (1 paper), Systemic Lupus Erythematosus Research (1 paper), Multiple Sclerosis Research Studies (1 paper) and COVID-19 diagnosis using AI (1 paper). The work is most often cited by research in Health Informatics (40 citations), Applied Microbiology and Biotechnology (29 citations), Health Information Management (36 citations), Family Practice (9 citations) and Psychiatry and Mental health (69 citations). Albert Buchard has collaborated with scholars based in France, United Kingdom and United States. Frequent co-authors include Pantelis Georgiou, Alison Holmes, Gabriel Birgand, Nathan Peiffer‐Smadja, Raheelah Ahmad, Timothy M. Rawson, François-Xavier Lescure, Daphné Bavelier, Pedro Cardoso-Leite and Mark S. Cohen. Their work appears in journals such as Clinical Microbiology and Infection, Epilepsy & Behavior, JAMA Network Open, Epilepsia and JAMA Neurology.

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.

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