Rapid and reliable computational markers of decision-making for predicting daily smoking behavior and smoking cessation treatment outcomes.

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Bibliographic Details
Title: Rapid and reliable computational markers of decision-making for predicting daily smoking behavior and smoking cessation treatment outcomes.
Authors: Lee JH; Department of Psychology, Seoul National University, Seoul, Republic of Korea., Lee SH; Department of Psychology, Seoul National University, Seoul, Republic of Korea.; School of Digital Humanities and Computational Social Sciences, KAIST, Daejeon, Republic of Korea., Yang J; Department of Psychology, Seoul National University, Seoul, Republic of Korea., Kim H; Department of Psychology, Seoul National University, Seoul, Republic of Korea., Pitt MA; Department of Psychology, The Ohio State University, Columbus, OH, USA., Park HJ; Center for Health Promotion, Samsung Medical Center, Seoul, Republic of Korea., Joh HK; Department of Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.; Department of Family Medicine, Seoul National University Health Service Center, Seoul, Republic of Korea.; Department of Family Medicine, Seoul National University Hospital, Seoul, Republic of Korea., Konova AB; Department of Psychiatry and the Brain Health Institute, Rutgers University, New Brunswick, NJ, USA. anna.konova@rutgers.edu., Ahn WY; Department of Psychology, Seoul National University, Seoul, Republic of Korea. wahn55@snu.ac.kr.; Department of Brain and Cognitive Sciences, Seoul National University, Seoul, Republic of Korea. wahn55@snu.ac.kr.; AI Institute, Seoul National University, Seoul, Republic of Korea. wahn55@snu.ac.kr.
Source: Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology [Neuropsychopharmacology] 2026 May 29. Date of Electronic Publication: 2026 May 29.
Publication Type: Journal Article
Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 8904907 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1740-634X (Electronic) Linking ISSN: 0893133X NLM ISO Abbreviation: Neuropsychopharmacology Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1740-634X
DOI:10.1038/s41386-026-02448-5