Kuniyoshi Hayashi

Abstract Recently, artificial intelligence methods have been applied in several fields, and their usefulness is attracting attention. These methods are techniques that correspond to models using batch and online processes. Because of advances in computational power, as represented by parallel computing, online techniques with several tuning parameters are widely accepted and demonstrate good results. Neural networks are representative online models for prediction and discrimination. Many online methods require large training data to attain sufficient convergence. Thus, online models may not converge effectively for low and noisy training datasets. For such cases, to realize effective learning convergence in online models, we introduce statistical insights into an existing method to set the initial weights of deep convolutional neural networks. Using an optimal similarity and resampling method, we proposed an initial weight configuration approach for neural networks. For a practice example, identification of biliary atresia (a rare disease), we verified the usefulness of the proposed method by comparing existing methods that also set initial weights of neural networks.

BACKGROUND: Non-disappearing subsolid nodules requiring follow-up are often detected during lung cancer screening, but changes in their invasiveness can be overlooked owing to slow growth. We aimed to develop a method for automatic identification of invasive tumors among subsolid nodules during multiple health check-ups using radiomics technology based on low-dose computed tomography (LD-CT) and examine its effectiveness. METHODS: We examined patients who underwent LD-CT screening from 2014 to 2019 and had lung adenocarcinomas resected after 5-year follow-ups. They were categorized into the invasive or less-invasive group; the annual growth/change rate (Δ) of the nodule voxel histogram using three-dimensional computed tomography (e.g., tumor volume, solid volume percentage, mean computed tomography value, variance, kurtosis, skewness, and entropy) was assessed. A discriminant model was designed through multivariate regression analysis with internal validation to compare its efficacy with that of a volume doubling time of <400 days. RESULTS: The study included 47 tumors (23 invasive, 24 less invasive), with no significant difference in the initial tumor volumes. Δskewness was identified as an independent predictor of invasiveness (adjusted odds ratio, 0.021; p=0.043), and when combined with Δvariance, it yielded high accuracy in detecting invasive lesions (88% true-positive, 80% false-positive). The detection model indicated surgery 2 years earlier than the volume doubling time, maintaining accuracy (median 3 years vs. 1 year before actual surgery, p=0.011). CONCLUSION: LD-CT radiomics showed promising potential in ensuring timely detection and monitoring of subsolid nodules that warrant follow-up over time.

Studies investigating the associations of oral function and dysphagia with frailty and sarcopenia in community-dwelling older adults are increasing; however, they have not been systematically summarized. We conducted a systematic review to investigate these associations. We searched electronic databases and synthesized relevant data using conventional (frequentist-style) and Bayesian meta-analyses. Twenty-four studies were found to be eligible for our review, including 20 cross-sectional and four prospective cohort studies. Older adults with frailty or sarcopenia had lower tongue pressure, according to the results of conventional meta-analysis (mean difference [95% confidence interval or credible interval]: -6.80 kPa [-10.22 to -3.38] for frailty and -5.40 kPa [-6.62 to -4.17] for sarcopenia) and Bayesian meta-analysis (-6.90 kPa [-9.0 to -4.8] for frailty, -5.35 kPa [-6.78 to -3.89] for sarcopenia). People with frailty had a higher odds ratio (OR) for dysphagia according to the results of conventional meta-analysis (3.99 [2.17 to 7.32]) and Bayesian meta-analysis (1.38 [0.77 to 1.98]). However, the results were inconclusive for people with sarcopenia. A prospective association could not be determined because of the lack of information and the limited number of studies. Decreased oral function and dysphagia can be important characteristics of frailty and sarcopenia in community-dwelling older adults.