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1. Genetic risk impacts the association of menopausal hormone therapy with colorectal cancer risk

2. Deepfake Detection: Leveraging the Power of 2D and 3D CNN Ensembles

3. Calcium intake and genetic variants in the calcium sensing receptor in relation to colorectal cancer mortality: an international consortium study of 18,952 patients

4. Fine-mapping analysis including over 254,000 East Asian and European descendants identifies 136 putative colorectal cancer susceptibility genes

5. Germline genetic regulation of the colorectal tumor immune microenvironment

7. Genome-Wide Interaction Analysis of Genetic Variants With Menopausal Hormone Therapy for Colorectal Cancer Risk.

8. Genome-wide interaction study of dietary intake of fibre, fruits, and vegetables with risk of colorectal cancer

9. Author Correction: Application of Mendelian randomization to explore the causal role of the human gut microbiome in colorectal cancer

10. Application of Mendelian randomization to explore the causal role of the human gut microbiome in colorectal cancer

13. Genome-wide interaction analysis of folate for colorectal cancer risk

15. The COronavirus Pandemic Epidemiology (COPE) Consortium: A Call to Action

16. Functional informed genome‐wide interaction analysis of body mass index, diabetes and colorectal cancer risk

18. Cross Age Face Generator: A Generative Adversarial Networks (GANs) Based Approach

19. Traffic Rule Violation Detection System: Deep Learning Approach

24. Novel Common Genetic Susceptibility Loci for Colorectal Cancer

26. Author Correction: Self-reported COVID-19 vaccine hesitancy and uptake among participants from different racial and ethnic groups in the United States and United Kingdom

27. Self-reported COVID-19 vaccine hesitancy and uptake among participants from different racial and ethnic groups in the United States and United Kingdom

29. Deep Learning-Based Smart Parking Management System and Business Model

30. An Empirical Comparison of Generative Adversarial Network (GAN) Measures

33. Supplementary Methods from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

34. Supplementary Table 2 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

35. Supplementary Figure 4 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

36. Data from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

37. Supplementary Table 1 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

38. Supplementary Figure 1 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

39. Supplementary Figure 2 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

40. Supplementary Figure 3 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

41. Supplementary Figure 5 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

42. Anosmia, ageusia, and other COVID-19-like symptoms in association with a positive SARS-CoV-2 test, across six national digital surveillance platforms: an observational study

43. Race, ethnicity, community-level socioeconomic factors, and risk of COVID-19 in the United States and the United Kingdom

44. Vaccine side-effects and SARS-CoV-2 infection after vaccination in users of the COVID Symptom Study app in the UK: a prospective observational study

47. Fine-mapping analysis including over 254 000 East Asian and European descendants identifies 136 putative colorectal cancer susceptibility genes

48. Attributes and predictors of long COVID

49. Dual-Core Implementation of Right-to-Left Modular Exponentiation

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