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Decoding Google Scholar: A Comprehensive Guide to Leveraging Python for Impactful Medical Research

Decoding Google Scholar: A Comprehensive Guide to Leveraging Python for Impactful Medical Research

"Decoding Google Scholar: A Comprehensive Guide to Leveraging Python for Impactful Medical Research" showcases how Python packages 'scholarly' and 'SerpApi' can mine data from Google Scholar profiles for medical research. 'Scholarly' extracts significant info such as a professor's name, affiliation, interests, citation count, and email domain. Despite occasional StopIteration errors, solutions like iterating through the search_query instead of using the next() function exist. SerpApi, a paid service, provides access to Google Scholar profile data similar to 'scholarly' but includes thumbnail images. However, researchers must respect ethical considerations and service terms when extracting and using this data. Python's 'scholarly' package and SerpApi offer researchers flexibility in their methods, contributing significantly to medical science, contingent on ethical compliance.

Full article here: https://ipllfirm.com/all-insights/news-and-articles/decoding-google-scholar-a-comprehensive-guide-to-leveraging-python-for-impactful-medical-research/