Interesting reads ... March 2023

Topics:?#DigitalTransformation, #Healthcare, #ArtificialIntelligence, #MachineLearning, #ML, #AI, #Medicine, #Hematology, #Oncology, #Design, #PublicHealth, #Radiology, #DALLE2, #Reimbursement

This paper explores the impact of digital transformation on the healthcare industry, specifically focusing on the emergence of platform ecosystems and their effects on the role of patients.

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This paper discusses the challenges faced when implementing artificial intelligence tools in clinical practice and presents principles based on the authors' experiences to address these challenges.

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The authors of this paper discuss how machines are already being used to augment the physician’s decision-making process, and postulate the potential impact of ML on medical practice and medical research based on its current capabilities and known limitations. Moreover, they discuss the feasibility of full machine autonomy in medicine.

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This paper presents a comprehensive overview of the current applications and future directions of artificial intelligence in hematology and oncology. The authors propose key recommendations for future directions and roadmap in integrating AI in hematology and oncology.

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Design is a craft and discipline that applies a specific mindset and skillset to a creative problem-solving process, enabling the development of informed, sensitive, inclusive, purposeful, appealing, and innovative solutions. The natural compatibility between public health and design has been under-appreciated.

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This paper provides expert commentary on the enablers and barriers to scaling up digital innovations in healthcare.

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This paper investigates change management and digital innovations in hospitals across five European countries. The authors conducted a survey among hospital managers and analyzed the results to identify the current state and challenges of digital transformation in healthcare.

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The authors of this paper believe that the introduction of AI and machine learning in medicine has helped health professionals improve the quality of care that they can deliver and has the promise to improve it even more in the near future and beyond.

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This study evaluates the capabilities of DALLE-2, an AI-powered image generation model, in the context of radiology. The authors aim to determine the model's potential for understanding and generating medical images relevant to radiology.

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The European Commission‘s Executive Agency for Small and Medium-sized Enterprises (EASME), the FDA‘s Digital Health Center for Excellence, and CMS all have recognized reimbursement for AI as a major priority. The approaches the authors of this paper describe can guide reimbursement policy to prioritize value and disincentivize overuse.

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