BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Sabre//Sabre VObject 4.5.8//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Europe/Zurich X-LIC-LOCATION:Europe/Zurich TZURL:http://tzurl.org/zoneinfo/Europe/Zurich BEGIN:DAYLIGHT TZOFFSETFROM:+0100 TZOFFSETTO:+0200 TZNAME:CEST DTSTART:19810329T020000 RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=-1SU END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0200 TZOFFSETTO:+0100 TZNAME:CET DTSTART:19961027T030000 RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=-1SU END:STANDARD END:VTIMEZONE BEGIN:VEVENT UID:news899@ub-easyweb.ub.unibas.ch DTSTAMP;TZID=Europe/Zurich:20260320T134234 DTSTART;TZID=Europe/Zurich:20260513T123000 SUMMARY:Beyond the search bar: Using AI to screen\, read\, and appraise sci entific literature DESCRIPTION:OverviewThe volume of scientific publications now exceeds what researchers can realistically screen\, read\, and critically evaluate. Thi s 15-minute Coffee Lecture presents a practical AI-supported workflow for navigating information overload—while maintaining methodological rigor.  We demonstrate how AI-powered discovery tools such as ResearchRabbit and Connected Papers expand exploration beyond keyword searches\, and how evi dence-oriented platforms like Consensus and scite.ai help assess how findi ngs are supported\, cited\, or contradicted in the broader literature. For screening\, active-learning systems such as ASReview and Rayyan can subst antially reduce title–abstract review time. For in-depth analysis\, RAG- based environments including Elicit and NotebookLM support structured read ing and semi-automated data extraction. Using predefined variables (e.g.\, sample size\, intervention characteristics\, primary outcomes)\, these sy stems can generate extraction tables and highlight potential methodologica l red flags—always requiring expert verification.  The session addresse s key concerns across disciplines\, including hallucinations\, algorithmic bias\, data protection\, and reproducibility. Participants will leave wit h immediately applicable tools and a clear understanding of where AI enhan ces scientific workflows—and where critical human appraisal remains indi spensable.\\r\\nLecturerDr. Robin Segerer\, Information specialist psychol ogy\\r\\n\\r\\nRegister here\\r\\nOverview Coffee Lectures Health & Scienc e in the Spring Semester 2026 X-ALT-DESC:

Overview
The volume of scientific publi cations now exceeds what researchers can realistically screen\, read\, and critically evaluate. This 15-minute Coffee Lecture presents a practical A I-supported workflow for navigating information overload—while maintaini ng methodological rigor.  \;We demonstrate how AI-powered discovery to ols such as ResearchRabbit and Connected Papers expand exploration beyond keyword searches\, and how evidence-oriented platforms like Consensus and scite.ai help assess how findings are supported\, cited\, or contradicted in the broader literature. For screening\, active-learning systems such as ASReview and Rayyan can substantially reduce title–abstract review time . For in-depth analysis\, RAG-based environments including Elicit and Note bookLM support structured reading and semi-automated data extraction. Usin g predefined variables (e.g.\, sample size\, intervention characteristics\ , primary outcomes)\, these systems can generate extraction tables and hig hlight potential methodological red flags—always requiring expert verifi cation.  \;The session addresses key concerns across disciplines\, inc luding hallucinations\, algorithmic bias\, data protection\, and reproduci bility. Participants will leave with immediately applicable tools and a cl ear understanding of where AI enhances scientific workflows—and where cr itical human appraisal remains indispensable.

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Lecturer
Dr. Robin Segerer\, Information specialist psychology

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Register here

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Ove rview Coffee Lectures Health &\; Science in the Spring Semester 2026

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