Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and memory loss, with few effective treatments currently available. The multifactorial nature of AD, shaped by genetic, environmental, and biological factors, complicates both research and clinical management. Recent advances in artificial intelligence (AI) and multi-omics technologies provide new opportunities to elucidate the molecular mechanisms of AD and identify early biomarkers for diagnosis and prognosis. AI-driven approaches such as machine learning, deep learning, and network-based models have enabled the integration of large-scale genomic, transcriptomic, proteomic, metabolomic, and microbiomic datasets. These efforts have facilitated the discovery of novel molecular signatures and therapeutic targets. Methods including deep belief networks and joint deep semi-non-negative matrix factorization have contributed to improvements in disease classification and patient stratification. However, ongoing challenges remain. These include data heterogeneity, limited interpretability of complex models, a lack of large and diverse datasets, and insufficient clinical validation. The absence of standardized multi-omics data processing methods further restricts progress. This review systematically summarizes recent advances in AI-driven multi-omics research in AD, highlighting achievements in early diagnosis and biomarker discovery while discussing limitations and future directions needed to advance these approaches toward clinical application.

Objective: “Food addiction” may be one of the drivers of the obesity epidemic. Bariatric surgery-induced weight loss can significantly alleviate food addiction in overweight or obese people. Appetite regulation is part of the feedback control system for energy balance. The purpose of this study was to investigate the effects of mobile application-based dietary intervention on weight-loss and food addiction in overweight and obese adults. Methods: A total of 101 overweight or obese people aged over 18 years, who were admitted to the obese multidisciplinary clinic of Ningbo First Hospital from August 2015 to January 2018 were enrolled. All subjects received health education and dietary guidance, and submitted their diet log through the weight management application of their smartphone. Over 12 weeks, a dietitian guided and corrected the subjects who did not meet the diet standards. Interviews, physical examinations, laboratory tests, and the Yale Food Addiction Scale Questionnaire survey were administered before and after the intervention (12 weeks) comparing subjects’ weight, food addiction symptom count, and the proportion of food addiction before and after intervention. Statistical analysis of body composition measurements, blood biochemical parameters, and symptom count scores was performed using paired data t-test, McNemar chi-square test, and Fisher’s exact test. Results: A total of 101 overweight and obese subjects were enrolled, including 31 males and 70 females, with an average age of (30.4±7.3) years, mean body mass index of (32.76±4.46) kg/m², and average body weight of (89.95±17.12) kg. The proportion of food addiction was 26.73%. After 12 weeks of dietary intervention with the mobile application, the number of people with food addiction decreased from 27 to 14, the proportion of food addiction decreased by 12.87%, the proportion of symptom counts ≥3 decreased from 41.58% to 19.80%.（χ²=5.17， 11.26, all P <0.01), and the symptom count decreased from 2.25 ±1.61 to 1.50±1.31 (t=3.64, P<0.001). Simultaneously, body weight, BMI, and waist circumference decreased by (6.54±1.03) kg, (2.35±0.36) kg/m², and (6.50±0.86) cm (t=6.36, 5.62 and 3.78, all P<0.001), respectively, compared with those before the intervention. Metabolic indicators such as fasting glucose, insulin resistance index, and LDL-C cholesterol also significantly improved, with a decrease of (0.38±0.10) mmol/L, 1.83±0.46, (0.22±0.75) mmol/L (t=3.67, 3.59, 2.97, all P<0.01). Conclusion The smartphone application-based dietary intervention can effectively improve blood glucose and lipid levels in overweight and obese people, reduce visceral fat accumulation and reduce insulin resistance, and improve the food addiction status of overweight and obese people.