A multi-model prediction of a stage-specific prognosis for colorectal cancer using attention-driven deep ensemble learning on genomic profiling data
IntroductionOver the decades, shifts in human lifestyle have led to alterations in dietary habits. The consumption of diets low in fiber and high in fat and sugar results in the production of carcinogenic metabolites during digestion. The food we consume undergoes a complex series of processes involving digestion and excretion, engaging various internal organs within the human body. The DNA and MiRNA present in food are crucial for sustaining human health. Damage to human organs can lead to the
Record details
Published: 21 July 2026
Source: Frontiers in Artificial Intelligence
Category: Research
Topics: Healthcare · Biotech
Retrieved: 22 July 2026
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ethics.ai (21 July 2026), “A multi-model prediction of a stage-specific prognosis for colorectal cancer using attention-driven deep ensemble learning on genomic profiling data,” evidence record 12404, https://ethics.ai/record/12404 (originally published by Frontiers in Artificial Intelligence).
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