Jimmy Lee
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Jimmy Lee has a total of 19 co-authors. Here are the top co-authors by number of shared publications:
Jie Yin Yee
Institute of Mental Health, Singapore, Singapore
2 shared publications- Wilson Wen Bin Goh
Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
2 shared publications Zixu Yang
Institute of Mental Health, Singapore, Singapore
2 shared publications- Brendon Yi Neng Wong
Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore
1 shared publication Eric Yu Hai Chen
Center for Youth Mental Health, University of Melbourne, Melbourne, Australia
1 shared publication- Irving Yu Le Shua
Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore
1 shared publication
Latest Publications
- Open Access
The Development and Validation of the Food Memory Bias Test for a Large-Scale Epidemiological Study in a Multiethnic Asian Population
Background: Memory influences decision-making regarding eating behaviour. However, marketing utilises our memory to exploit our consumptive habits. Whether we have an inherent bias towards memorising visual cues associated with high-calorie foods and how such bias contributes to our health outcomes remains to be determined. We therefore aimed to develop and validate a computerized, image-based Food Memory Bias Task (FMBT) for use in multiethnic Asian populations. Methods: In the development phase involving 172 participants, 91.9% rated the instrument as user-friendly and we optimised the instrument format into 12 visual food cues and 30-min delay period to avoid a ceiling effect. In the validation phase involving 184 multi-ethnic Asian participants (49.3 (14.5) years old, 44.6% male, 71.7% Chinese), FMBT memory score was associated with the brief assessment of cognition memory (β(p) = 0.23 (5.1 × 10−6)), and general cognition score ‘g’ (β(p) = 0.30 (6.5 × 10−9)). Results: Higher memory bias was associated with lower memory score in the low-calorie bias group (, ), but not in the hig h-calorie bias group. In this present study, despite randomly administering two versions of the test across visits, the FMBT bias score demonstrates a significant learning effect and low reproducibility (r(p) = −0.14 (0.11) across visits). Food memory bias score is associated with higher food approach traits according to the Adult-Eating Behaviour Questionnaire (β(p) = 0.23(0.015)), independent of age, sex, and ethnicity. Conclusion: FMBT provides an opportunity to address epidemiological questions on how food memory bias influences dietary habit and cardiometabolic health, and how it is in turn shaped by our built environment.Open AccessThe Development and Validation of the Food Memory Bias Test for a Large-Scale Epidemiological Study in a Multiethnic Asian Population
Background: Memory influences decision-making regarding eating behaviour. However, marketing utilises our memory to exploit our consumptive habits. Whether we have an inherent bias towards memorising visual cues associated with high-calorie foods and how such bias contributes to our health outcomes remains to be determined. We therefore aimed to develop and validate a computerized, image-based Food Memory Bias Task (FMBT) for use in multiethnic Asian populations. Methods: In the development phase involving 172 participants, 91.9% rated the instrument as user-friendly and we optimised the instrument format into 12 visual food cues and 30-min delay period to avoid a ceiling effect. In the validation phase involving 184 multi-ethnic Asian participants (49.3 (14.5) years old, 44.6% male, 71.7% Chinese), FMBT memory score was associated with the brief assessment of cognition memory (β(p) = 0.23 (5.1 × 10−6)), and general cognition score ‘g’ (β(p) = 0.30 (6.5 × 10−9)). Results: Higher memory bias was associated with lower memory score in the low-calorie bias group (, ), but not in the hig h-calorie bias group. In this present study, despite randomly administering two versions of the test across visits, the FMBT bias score demonstrates a significant learning effect and low reproducibility (r(p) = −0.14 (0.11) across visits). Food memory bias score is associated with higher food approach traits according to the Adult-Eating Behaviour Questionnaire (β(p) = 0.23(0.015)), independent of age, sex, and ethnicity. Conclusion: FMBT provides an opportunity to address epidemiological questions on how food memory bias influences dietary habit and cardiometabolic health, and how it is in turn shaped by our built environment. - Open Access
- 20 August 2026
- Published by Springer Nature in npj Mental Health Research
Emotion-informed associative learning in large language models for mental health detection from speech
- 20 August 2026
- Published by Springer Nature in npj Mental Health Research
Open AccessEmotion-informed associative learning in large language models for mental health detection from speech
- Open Access
- 30 March 2026
- Published by Springer Nature in Translational Psychiatry
- Vol. 16 (1)
Blood plasma proteomic biomarkers for forecasting transition to psychosis in an Asian cohort
Plasma proteomic biomarkers hold significant promise for enhancing clinical assessments and improving early detection of psychosis conversion; however, concerns about their reproducibility and generalizability persist. Previous studies, largely conducted in Caucasian cohorts, have identified proteomic biomarkers predictive of psychosis conversion in individuals at ultra-high risk (UHR) of psychosis. In this study, we acquired plasma proteomics data from an Asian UHR cohort, the Longitudinal Youth at Risk Study (LYRIKS). We established a robust machine learning framework, through which we developed and evaluated prediction models for psychosis conversion. We showed that proteomic signatures previously identified in a predominantly Caucasian UHR cohort generalized to the LYRIKS cohort (best AUC = 0.81). Furthermore, we developed three prediction models using the LYRIKS dataset that demonstrated superior performance (best AUC = 0.96). Through these models, we identified novel proteomic signatures with high predictive performance. Despite the differences in individual protein composition between Asian- and Caucasian-derived signatures, functional convergence was observed across key pathways and protein families, namely the complement and coagulation cascade, apolipoproteins, inter-alpha-trypsin inhibitor heavy chain proteins, and serine protease inhibitors. Although current literature is divided on the utility of blood plasma biomarkers in psychiatric diagnosis, our study supports their use by demonstrating cross-population generalizability of Caucasian-derived signatures and deriving signatures with high predictive value from an Asian cohort that converge functionally.
- 30 March 2026
- Published by Springer Nature in Translational Psychiatry
- Vol. 16 (1)
Open AccessBlood plasma proteomic biomarkers for forecasting transition to psychosis in an Asian cohort
Plasma proteomic biomarkers hold significant promise for enhancing clinical assessments and improving early detection of psychosis conversion; however, concerns about their reproducibility and generalizability persist. Previous studies, largely conducted in Caucasian cohorts, have identified proteomic biomarkers predictive of psychosis conversion in individuals at ultra-high risk (UHR) of psychosis. In this study, we acquired plasma proteomics data from an Asian UHR cohort, the Longitudinal Youth at Risk Study (LYRIKS). We established a robust machine learning framework, through which we developed and evaluated prediction models for psychosis conversion. We showed that proteomic signatures previously identified in a predominantly Caucasian UHR cohort generalized to the LYRIKS cohort (best AUC = 0.81). Furthermore, we developed three prediction models using the LYRIKS dataset that demonstrated superior performance (best AUC = 0.96). Through these models, we identified novel proteomic signatures with high predictive performance. Despite the differences in individual protein composition between Asian- and Caucasian-derived signatures, functional convergence was observed across key pathways and protein families, namely the complement and coagulation cascade, apolipoproteins, inter-alpha-trypsin inhibitor heavy chain proteins, and serine protease inhibitors. Although current literature is divided on the utility of blood plasma biomarkers in psychiatric diagnosis, our study supports their use by demonstrating cross-population generalizability of Caucasian-derived signatures and deriving signatures with high predictive value from an Asian cohort that converge functionally.