Welcome to episode five of the AI Report. In this episode, we focus on two critical areas: heart failure treatment and emergency room triage. Discover how AI tools are revolutionizing the management of heart failure, improving patient outcomes, and reducing costs. We also explore how AI surpasses human clinicians in accurately prioritizing patients in emergency situations. Tune in and witness the AI revolution in heart failure and emergency triage!

Identifying subtypes of heart failure from three electronic health record sources with machine learning: an external, prognostic, and genetic validation study - The Lancet Digital Health

ESOC2024 - European Stroke Organisation (eso-stroke.org)

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In this episode, we explore the exciting developments happening in the field of healthcare, where AI is playing a critical role in detecting and treating illnesses. From predicting cancer outcomes to Parkinsons disease detection, AI is changing the way we approach healthcare. Join us as we discuss the latest research and applications in computer vision, machine learning, and data analytics. Don't miss out on this fascinating journey into the future of healthcare.

A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories | Nature Medicine

Machine learning for diagnosis of myocardial infarction using cardiac troponin concentrations | Nature Medicine

Parkinsonism & Related Disorders (prd-journal.com)

JCM | Free Full-Text | Development of a Reinforcement Learning Algorithm to Optimize Corticosteroid Therapy in Critically Ill Patients with Sepsis (mdpi.com)

Uncovering the spatial landscape of molecular interactions within the tumor microenvironment through latent spaces: Cell Systems

Automated Assessment of Cardiac Systolic Function From Coronary Angiograms With Video-Based Artificial Intelligence Algorithms | Cardiology | JAMA Cardiology | JAMA Network

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In this episode of the AI Report podcast, we discuss how AI is being used to improve the accuracy and efficiency of detecting heart disease from medical imaging, and how it can optimize the design of mRNA vaccines for COVID-19. We also cover how AI is transforming the field of oncology, from personalized treatment to drug discovery, and how it is revolutionizing radiology, from enhancing the speed and accuracy of diagnoses to improving patient outcomes. Tune in to learn about the latest applications of AI in healthcare and the significant impact it can have on improving patient care.

Discord: https://discord.gg/9SeSJz5Vds

Gene therapy reverses vision loss in primates (freethink.com)

Bird Flu's Surge Has Scientists Seeking Clues to Prevent the Next Pandemic (yahoo.com)

Brain activity decoder can reveal stories in people's minds (medicalxpress.com)

AI bias may impair radiologist accuracy on mammogram (medicalxpress.com)

Artificial intelligence may predict heart attacks (medicalxpress.com)

New AI algorithm could boost COVID-19 mRNA vaccine antibody response by 128 times (medicalxpress.com)

AI helpful in triaging breast masses in low-resource areas (medicalxpress.com)

Artificial intelligence detects fractures on CT images for osteoporosis diagnostics (medicalxpress.com)

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Welcome to this episode of the AI Report, where we explore the latest developments in artificial intelligence in healthcare. This week's articles address important issues in the field of healthcare AI, from fairness to accuracy and the role of clinicians in decision-making. Join us as we delve into these topics and discuss the potential of AI to improve patient outcomes and transform healthcare as we know it.

Discord: Discord: https://discord.gg/9SeSJz5Vds

Links to articles:

Frontiers | Validation of clinical acceptability of deep-learning-based automated segmentation of organs-at-risk for head-and-neck radiotherapy treatment planning (frontiersin.org)

Ignore, Trust, or Negotiate: Understanding Clinician Acceptance of AI-Based Treatment Recommendations in Health Care (arxiv.org)

Development and international validation of custom-engineered and code-free deep-learning models for detection of plus disease in retinopathy of prematurity: a retrospective study - The Lancet Digital Health

Toward fairness in artificial intelligence for medical image analysis: identification and mitigation of potential biases in the roadmap from data collection to model deployment (spiedigitallibrary.org)

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In this episode, we cover a range of topics including a new study on an online tool for assessing dementia risk, and a new tool for predicting the effects of genetic mutations in disease genes. We also discuss a new AI algorithm that improves the ability of electronic devices to detect coughing and a study on the use of the DELPHI method to obtain expert consensus on rules for creating a digital twin model of acute ischemic stroke. This episode provides an informative and engaging overview of recent developments in AI and healthcare.

Discord: https://discord.gg/9SeSJz5Vds

Links to articles discussed in the show:

Online tool found to be effective at assessing dementia risk | UNSW Newsroom

New tool facilitates clinical interpretation of genetic information: MPI-CBG

Researchers Help AI Express Uncertainty to Improve Health Monitoring Tech | NC State News (ncsu.edu)

Developing DELPHI expert consensus rules for a digital twin model of acute stroke care in the neuro critical care unit | BMC Neurology | Full Text (biomedcentral.com)

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