Revamping AI Models in Dermatology: Overcoming Critical Challenges for Enhanced Skin Lesion Diagnosis

The surge in developing deep learning models for diagnosing skin lesions through image analysis is notable, yet their clinical black faces challenges. Current dermatology AI models have limitations: limited number of possible diagnostic outputs, lack of real-world testing on uncommon skin lesions, inability to detect out-of-distribution images, and over-reliance on dermoscopic images. To address these, we present an All-In-One \textbf{H}ierarchical-\textbf{O}ut of Distribution-\textbf{C}linical Triage (HOT) model. For a clinical image, our model generates three outputs: a hierarchical prediction, an alert for out-of-distribution images, and a recommendation for dermoscopy if clinical image alone is insufficient for diagnosis. When the recommendation is pursued, it integrates both clinical and dermoscopic images to deliver final diagnosis. Extensive experiments on a representative cutaneous lesion dataset demonstrate the effectiveness and synergy of each component within our framework. Our versatile model provides valuable decision support for lesion diagnosis and sets a promising precedent for medical AI applications

Implementing novel models of posttreatment care for cancer survivors: Enablers, challenges and recommendations

AIM: The American Society of Clinical Oncology and US Institute of Medicine emphasize the need to trial novel models of posttreatment care, and disseminate findings. In 2011, the Victorian State Government (Australia) established the Victorian Cancer Survivorship Program (VCSP), funding six 2-year demonstration projects, targeting end of initial cancer treatment. Projects considered various models, enrolling people of differing cancer types, age and residential areas. We sought to determine common enablers of success, as well as challenges/barriers. METHODS: Throughout the duration of the projects, a formal "community of practice" met regularly to share experiences. Projects provided regular formal progress reports. An analysis framework was developed to synthesize key themes and identify critical enablers and challenges. Two external reviewers examined final project reports. Discussion with project teams clarified content. RESULTS: Survivors reported interventions to be acceptable, appropriate and effective. Strong clinical leadership was identified as a critical success factor. Workforce education was recognized as important. Partnerships with consumers, primary care and community organizations; risk stratified pathways with rapid re-access to specialist care; and early preparation for survivorship, self-management and shared care models supported positive project outcomes. Tailoring care to individual needs and predicted risks was supported. Challenges included: lack of valid assessment and prediction tools; limited evidence to support novel care models; workforce redesign; and effective engagement with community-based care and issues around survivorship terminology. CONCLUSION: The VCSP project outcomes have added to growing evidence around posttreatment care. Future projects should consider the identified enablers and challenges when designing and implementing survivorship care

The Effects of Room Management and Small-group Procedures on the Behaviour of Older Adults who have Alzheimer's Disease.

The effects of room management and small groups procedures on the behavior of five older adults with Alzheimer’s Disease was experimentally evaluated by a multielement design with replications across five subjects. Engagement during both room management and small groups was higher than during no treatment baselines. The effects on affective and maladaptive behaviors were of small magnitude. Evidence of individual differences was found both with respect to absolute proportions of time spent in various behaviors and with respect to interactions between individual differences and experimental conditions