Generating research hypotheses to overcome key challenges in the early diagnosis of colorectal cancer - Future application of AI

Abstract

We intend to explore the capability of ChatGPT 4.0 in generating innovative research hypotheses to address key challenges in the early diagnosis of colorectal cancer (CRC). We asked ChatGPT to generate hypotheses focusing on three main challenges: improving screening accuracy, overcoming technological limitations, and identifying reliable biomarkers. The hypotheses were evaluated for novelty. The experimental plans provided by ChatGPT for selected hypotheses were assessed for completion and feasibility. As a result, ChatGPT generated a total of 65 hypotheses. ChatGPT rated all 65 hypotheses, with 25 hypotheses receiving the highest rating (5) and 40 hypotheses receiving a rating of 4 or lower. The research team evaluated a total of 65 hypotheses, assigning them the following grades: hypotheses were rated as excellent (Grade 5), 16 were deemed suitable (Grade 4), 31 were classified as satisfactory (Grade 3), 12 were identified as needing Improvement (Grade 2), and one was considered poor (Grade 1). Additionally, the study determined that 17 of the generated hypotheses had corresponding publications. Out of the three experimental plans assessed, one was rated excellent (5) for feasibility, while the others received good (4) and moderate (3) ratings. Predicted outcomes and alternative approaches were rated as good, with some areas requiring further improvement. Our data demonstrate that AI has the potential to revolutionize hypothesis generation in medical research, though further validation through experimental and clinical studies is needed. This study suggests that while AI can generate novel hypotheses, human expertise is essential for evaluating their practicality and relevance in scientific research.