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Background: Although lesion counting is an evaluation method that effectively analyzes facial acne severity, its usage is limited because of difficult implementation. Objectives: We aimed to develop and validate an automated algorithm that detects and counts acne lesions by type, and to evaluate its clinical applicability as an assistance tool through a reader test. Methods: A total of 20,699 lesions (closed and open comedones, papules, nodules/cysts, and pustules) were manually labeled on 1213 facial images of 398 facial acne photography sets (frontal and both lateral views) acquired from 258 patients and used for training and validating algorithms based on a convolutional neural network for classifying five classes of acne lesions or for binary classification into noninflammatory and inflammatory lesions. Results: In the validation dataset, the highest mean average precision was 28.48 for the binary classification algorithm. Pearson's correlation of lesion counts between algorithm and ground-truth was 0.72 (noninflammatory) and 0.90 (inflammatory), respectively. In the reader test, eight readers (100.0%) detected and counted lesions more accurately using the algorithm compared with the reader-alone evaluation. Conclusions: Overall, our algorithm demonstrated clinically applicable performance in detecting and counting facial acne lesions by type and its utility as an assistance tool for evaluating acne severity. [ABSTRACT FROM AUTHOR]

Purpose: Sarcopenia is an involuntary loss of muscle mass, strength, and physical performance associated with aging. Sarcopenia contributes to adverse health outcomes. Milk contains essential amino acids important for maintaining muscle. We investigated the relationships among milk consumption frequency (MCF), muscle mass, and strength in Korean adults. Methods: We analyzed the data from 16,173 adults in the 2008–2011 Korean National Health and Nutrition Examination Survey (KNHANES), 13,537 adults in the 2014–2016 KNHANES, and 8254 adults in the Korean Genome and Epidemiology Study (KoGES). MCF was divided into two groups: (1) MCF less than once per day (MCF < 1 group) and (2) MCF greater than or equal to once per day (MCF ≥ 1 group). Low skeletal muscle mass index (LSMI) was defined using the Foundation for the National Institutes of Health sarcopenia project criteria for low muscle mass. Muscle strength was measured using the hand-grip strength test. Results: The odds ratio (95% confidence interval) for LSMI in the MCF < 1 group was 1.250 (1.013–1.543) after adjusting for confounding factors, compared with the MCF ≥ 1 group (2008–2011 KNHANES). The adjusted mean for hand-grip strength was higher in the MCF ≥ 1 group (2014–2016 KNHANES). After a mean follow-up of 9 years, fat-free mass/body mass index was higher in the MCF ≥ 1 group than the MCF < 1 group (KoGES). Conclusion: We found that MCF ≥ 1 was significantly associated with higher skeletal muscle index and muscle strength than lower MCF. Milk consumption could help prevent sarcopenia in adults. [ABSTRACT FROM AUTHOR]