Isotta Landi

559 total citations
18 papers, 227 citations indexed

About

Isotta Landi is a scholar working on Social Psychology, Cognitive Neuroscience and Artificial Intelligence. According to data from OpenAlex, Isotta Landi has authored 18 papers receiving a total of 227 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Social Psychology, 5 papers in Cognitive Neuroscience and 5 papers in Artificial Intelligence. Recurrent topics in Isotta Landi's work include Autism Spectrum Disorder Research (5 papers), Bayesian Methods and Mixture Models (2 papers) and Machine Learning in Healthcare (2 papers). Isotta Landi is often cited by papers focused on Autism Spectrum Disorder Research (5 papers), Bayesian Methods and Mixture Models (2 papers) and Machine Learning in Healthcare (2 papers). Isotta Landi collaborates with scholars based in United States, Italy and United Kingdom. Isotta Landi's co-authors include Girish N. Nadkarni, Akhil Vaid, Alexander W. Charney, Paola Venuti, Ismail Nabeel, Eyal Klang, Mahmud Omar, Shelly Soffer, Michael Lombardo and Edgar Argulian and has published in prestigious journals such as Psychological Medicine, Molecular Psychiatry and Frontiers in Psychology.

In The Last Decade

Isotta Landi

17 papers receiving 226 citations

Peers

Isotta Landi

CCM

Nienke Schutte Netherlands

Johan H. Thygesen United Kingdom

Lucía A. Carrasco‐Ribelles Spain

Vijay Yadav United States

Sashank Kaushik United States

Vy Pham United States

Brianna M. Goodale United States

Davide Barbieri Italy

Georg Starke Switzerland

David Musheyev United States

Nienke Schutte Netherlands

Isotta Landi

80 ×1.3

CCM

27 ×0.5

8 ×0.2

21 ×0.6

16 ×0.5

Citations per year, relative to Isotta Landi Isotta Landi (= 1×) peers Nienke Schutte

Countries citing papers authored by Isotta Landi

Since Specialization

Citations

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

Fields of papers citing papers by Isotta Landi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Isotta Landi

This figure shows the co-authorship network connecting the top 25 collaborators of Isotta Landi. A scholar is included among the top collaborators of Isotta Landi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Isotta Landi. Isotta Landi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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18 of 18 papers shown

Patra, Braja Gopal, Lauren Lepow, Mohit Sharma, et al.. (2024). Extracting social support and social isolation information from clinical psychiatry notes: comparing a rule-based natural language processing system and a large language model. Journal of the American Medical Informatics Association. 32(1). 218–226. 6 indexed citations

Landi, Isotta, Massimo Molteni, Maria Nobile, et al.. (2024). Enhanced motor noise in an autism subtype with poor motor skills. Molecular Autism. 15(1). 36–36. 4 indexed citations

Omar, Mahmud, Shelly Soffer, Alexander W. Charney, et al.. (2024). Applications of large language models in psychiatry: a systematic review. Frontiers in Psychiatry. 15. 1422807–1422807. 26 indexed citations

Omar, Mahmud, Shelly Soffer, Alexander W. Charney, et al.. (2024). Applications of Large Language Models in Psychiatry: A Systematic Review. medRxiv. 6 indexed citations

Landi, Isotta, et al.. (2023). Prognostic early snapshot stratification of autism based on adaptive functioning. Nature Mental Health. 1(5). 327–336. 10 indexed citations

Vaid, Akhil, Isotta Landi, Girish N. Nadkarni, & Ismail Nabeel. (2023). Using fine-tuned large language models to parse clinical notes in musculoskeletal pain disorders. The Lancet Digital Health. 5(12). e855–e858. 26 indexed citations

Coombes, Brandon J., Isotta Landi, Karmel W. Choi, et al.. (2023). The genetic contribution to the comorbidity of depression and anxiety: a multi-site electronic health records study of almost 178 000 people. Psychological Medicine. 53(15). 7368–7374. 8 indexed citations

Amato, Marco, Ahmed Eissa, Stefano Puliatti, et al.. (2021). Feasibility of a telementoring approach as a practical training for transurethral enucleation of the benign prostatic hyperplasia using bipolar energy: a pilot study. World Journal of Urology. 39(9). 3465–3471. 6 indexed citations

Lombardo, Michael, Laura Schreibman, Aubyn C. Stahmer, et al.. (2021). Pre-treatment clinical and gene expression patterns predict developmental change in early intervention in autism. Molecular Psychiatry. 26(12). 7641–7651. 9 indexed citations

10.

Vaid, Akhil, Kipp W. Johnson, Marcus A. Badgeley, et al.. (2021). Using Deep-Learning Algorithms to Simultaneously Identify Right and Left Ventricular Dysfunction From the Electrocardiogram. JACC. Cardiovascular imaging. 15(3). 395–410. 60 indexed citations

11.

Coombes, Brandon J., Isotta Landi, Gregory D. Jenkins, et al.. (2021). POLYGENIC RISK OF COMORBID ANXIETY AND DEPRESSION ACROSS HEALTH SYSTEMS. European Neuropsychopharmacology. 51. e31–e32.

12.

Somani, Sulaiman, Hossein Honarvar, Sukrit Narula, et al.. (2021). Development of a machine learning model using electrocardiogram signals to improve acute pulmonary embolism screening. European Heart Journal - Digital Health. 3(1). 56–66. 19 indexed citations

13.

Landi, Isotta, et al.. (2021). reval: A Python package to determine best clustering solutions with stability-based relative clustering validation.. Apollo (University of Cambridge). 6 indexed citations

14.

Landi, Isotta, et al.. (2020). reval: a Python package to determine the best number of clusters with stability-based relative clustering validation.. arXiv (Cornell University). 1 indexed citations

15.

Mazzoni, Noemi, Isotta Landi, Paola Ricciardelli, Rossana Actis-Grosso, & Paola Venuti. (2020). “Motion or Emotion? Recognition of Emotional Bodily Expressions in Children With Autism Spectrum Disorder With and Without Intellectual Disability”. Frontiers in Psychology. 11. 478–478. 16 indexed citations

16.

Landi, Giulia, Elena Simoni, Isotta Landi, et al.. (2020). Therapeutic Factors in a Psychiatric Group Therapy: a Preliminary Validation of Therapeutic Factors Inventory-8, Italian Version. Psychiatric Quarterly. 92(2). 523–536. 1 indexed citations

17.

Landi, Isotta, Michele Giannotti, Paola Venuti, & Simona de Falco. (2019). Maternal and family predictors of infant psychological development in at‐risk families: A multilevel longitudinal study. Research in Nursing & Health. 43(1). 17–27. 7 indexed citations

18.

Venuti, Paola, Arianna Bentenuto, Isotta Landi, et al.. (2016). A joint behavioral and emotive analysis of synchrony in music therapy of children with autism spectrum disorders. Health Psychology Report. 5(2). 162–172. 16 indexed citations

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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