Real-world experience with a treatment with a skincare regimen of products containing the Macrocystis pyrifera ferment for optimizing facial skin rejuvenation.

BACKGROUND: Specialized aesthetic skincare treatments are an important part of helping reduce facial signs of aging. AIMS: This article highlights real-world experience with a Macrocystis pyrifera ferment-containing skincare regimen comprising a cleansing foam, a serum, and a moisturizer with anti-aging, anti-inflammatory, anti-erythema, and healing properties for facial skin condition improvement. PATIENTS/METHODS: The real-world case (RWC) series presented highlights and the expert panel's clinical experience with the M. pyrifera ferment-containing skincare regimen used for 12 weeks to improve facial skin conditions. The panelists convened a meeting to discuss and select RWCs from their practice using the M. pyrifera ferment-containing skincare regimen. RESULTS: The RWC series showed that erythema and inflamed, easily irritated skin bother patients, even when it is mild. Reducing inflammation, erythema, and visible signs of facial aging and improving skin health contributed to patient satisfaction. CONCLUSION: The M. pyrifera ferment-containing skincare regimen comprising a cleansing foam, a serum, and a moisturizer is effective in decreasing the visible effects of inflammation and signs of aging while promoting healing by enhancing barrier resilience and recovery.

Application of Artificial Intelligence-Based Technologies in the Healthcare Industry: Opportunities and Challenges.

This study examines the current state of artificial intelligence (AI)-based technology applications and their impact on the healthcare industry. In addition to a thorough review of the literature, this study analyzed several real-world examples of AI applications in healthcare. The results indicate that major hospitals are, at present, using AI-enabled systems to augment medical staff in patient diagnosis and treatment activities for a wide range of diseases. In addition, AI systems are making an impact on improving the efficiency of nursing and managerial activities of hospitals. While AI is being embraced positively by healthcare providers, its applications provide both the utopian perspective (new opportunities) and the dystopian view (challenges to overcome). We discuss the details of those opportunities and challenges to provide a balanced view of the value of AI applications in healthcare. It is clear that rapid advances of AI and related technologies will help care providers create new value for their patients and improve the efficiency of their operational processes. Nevertheless, effective applications of AI will require effective planning and strategies to transform the entire care service and operations to reap the benefits of what technologies offer.

Preclinical curriculum of prospective case-based teaching with faculty- and student-blinded approach.

BACKGROUND: Case-based teaching with real patient cases provides benefit of simulating real-world cognition. However, while clinical practice involves a prospective approach to cases, preclinical instruction typically involves full disclosure of case content to faculty, introducing hindsight bias into faculty teaching in medical curricula. METHODS: During 2015-2018, we piloted an optional medical school curriculum involving 6-7 one-hour sessions over a 3-month period each year. New groups enrolled each year from first- and second-year classes. A facilitator provided a blinded physician discussant and blinded students with case information during and not in advance of each session, allowing prospective case-based discussions. Cases were based on real patients treated in the Department of Medicine. Clinical material was presented in the chronologic sequence encountered by treating physicians. Content covered a median of 5 patient visits/case (range: 2-10) spanning over months. A 14-item survey addressing components of the reporter-interpreter-manager-educator (RIME) scheme was developed and used to compare self-reported clinical skills between course participants and non-participant controls during the 2016 course iteration. RESULTS: This elective curriculum at Stanford School of Medicine involved 170 preclinical students (22.7% of 750 eligible). During the 2016 course iteration, a quasi-experimental study compared self-reported clinical skills between 29 course participants (response rate: 29/49 [59.2%]) and 35 non-participant controls (response rate: 35/132 [26.5%]); students self-assessed clinical skills via the RIME-based survey developed for the course. Two-sample t-tests compared the change in pre- and post-course skills between course participants and non-participants. Of 15 Department of Medicine faculty members invited as discussants, 12 (80%) consented to participate. Compared with controls, first-year participants self-assessed significantly greater improvement in understanding how clinicians reason through cases step-by-step to arrive at diagnoses (P = 0.049), work through cases in longitudinal settings (P = 0.049), and share information with patients (P = 0.047). Compared with controls, second-year participants self-assessed significantly greater improvement (P = 0.040) in understanding how clinicians reason through cases step-by-step to arrive at diagnoses. CONCLUSIONS: Prospective case-based discussions with blinding of faculty and students to clinical content circumvents hindsight bias and may impart real-world cognitive skills as determined by student self-report.