Interesting reads ... June 2023
Pranav Rajpurkar and Matthew Lungren MD MPH present an insightful discussion on the prospects and challenges of AI interpretation of medical images, emphasizing the potential of AI models to accurately generate full radiologic reports and highlighting the significance of clinician-AI collaboration. They underscore the necessity of increased transparency, robust generalization checks, and post-deployment monitoring for successful integration of AI in healthcare, along with the development of new foundational models.
Samaneh (Sam) Madanian , Ivana Nakarada-Kordic , Stephen Reay, and T'heniel Chetty provide a thorough analysis of patients' views on digital health tools, elucidating the factors influencing their acceptance, the challenges encountered, and their expectations. They highlight patients' appreciation for the convenience of these tools and emphasize the need for user-friendly design, while also pointing out concerns about privacy, data security, and the impersonal nature of digital interactions.
D-Q Wang, L-Y Feng, J-G Ye, J-G Zou, and Y-F Zheng present a comprehensive discussion on the potential of large-scale AI models like ChatGPT in biomedical research and healthcare, outlining their application in protein sequence analysis, drug molecule study, disease diagnosis, and patient monitoring. They underscore the need for fine-tuning these models on medical-specific datasets to enhance their performance in the medical domain and highlight the significant roles of Large Language Models (LLMs), Vision-Language Models (VLMs), Graph Language Models (GLMs), and Language-conditioned Multiagent Models (LLMMs).
Jordan Silberman, MD, PhD and colleagues present the Evidence DEFINED framework, a novel, multidisciplinary approach for evaluating digital health interventions (DHIs) designed to be both rigorous and fast-paced, matching the swift evolution of the digital health landscape. The framework is developed to reliably identify clinically valuable DHIs and accommodate rapid market introductions, addressing the pressing need for an efficient and thorough assessment strategy in a burgeoning field of health technologies.
In their 2011 paper, authors Pim Kuipers , Elizabeth Kendall AM GAICD , Ehrlich, Michelle Mcintyre, Barber, Delena Amsters, Heidi Muenchberger, and Sharon Brownie explore how the intertwining complexities of health conditions, patient circumstances, and healthcare systems pose significant challenges for health services and practitioners, often leading to confusing care pathways and resource allocation. They argue for the necessity of flexible skills, innovative thinking, and comprehensive training in the healthcare workforce to effectively address the needs of patients with complex health situations.
This paper by Karan Singhal et al. explores the potential of Large Language Models (LLMs) in the medical field, demonstrating their ability to answer medical questions accurately. They introduce the MultiMedQA benchmark and discuss the importance of fine-tuning and safety considerations for LLMs in the medical domain. The study provides valuable insights into the capabilities and limitations of LLMs and proposes future research directions.
Recommended by LinkedIn
In this paper by Manas Dave and Neil Patel, the integration of artificial intelligence in healthcare education is explored. The authors discuss the potential benefits of AI in enhancing the learning experience and improving patient care through virtual simulations and personalized treatment plans. They also address the challenges of maintaining human touch and empathy, as well as the risk of over-reliance on AI and the need for critical thinking skills. The paper provides a comprehensive overview of the topic, offering insights for healthcare professionals and educators interested in leveraging AI effectively in healthcare education.
Gabrielle Chenais , Emmanuel Lagarde, and Cedric Gil-Jardine critically explore the utilization and potential of AI in various facets of emergency medical services, from self-triage to emergency department operations, highlighting its potential to enhance efficiency and accuracy. They also delve into the ethical, legal aspects and possible biases in AI applications, emphasizing the significance of explainability, interpretability, and careful bias consideration to ensure safe and effective use in emergency medical services.
In their paper, Joana Carrilho , Diogo Videira Henriques , Claudia Campos , Luís Midão , and Elísio Costa advocate for a shift towards a user-centered, collaborative model in health and care services that harnesses open innovation. They propose a dynamic and adaptive "Collaborative Ecosystem" that integrates multiple societal sectors, underlines the necessity for digital health literacy, self-management, and long-term stakeholder engagement, aiming to address the challenges posed by lifestyle-related illnesses and an aging population.
In their extensive examination of cancer statistics in the United States, Rebecca Siegel , Kimberly Miller , Hannah Fuchs , and Ahmedin Jemal project 1,918,030 new cancer cases and 609,360 deaths for 2022, with lung cancer causing about 350 deaths per day. The study analyzes the trends in incidence and mortality rates for different types of cancer, noting a slow rise in breast cancer cases, stability in overall prostate cancer but increase in advanced cases, a sharp decline in advanced lung cancer incidence contrasted by a sudden rise in localized-stage diagnoses, and mortality patterns closely reflecting the incidence trends.
For more, follow me on LinkedIn & Twitter. 🚀✨
Audiobook author. Photographer. Fully trained missionary.
1yGlad to be here
Business Growth Strategist, Deep Thinker & Finder of Innovation Gold (rasey.com)
1yFantastic way to document readings
Realtor Associate @ Next Trend Realty LLC | HAR REALTOR, IRS Tax Preparer
1yThanks for Sharing.
Medical Doctor - Nephrologist - Freelance Consultant at EPISTEMIX
1y====>>>> Chiara Sgarbossa