New & Notable
Deep learning shows promise in predicting osteoporosis risk
A deep neural network significantly outperformed existing machine learning and regression models for osteoporosis risk prediction in a cohort of over 8,000 participants.
Advancing transparency, fairness in AI to boost health equity
Fairness in clinical algorithms is key to mitigating race-based health inequity. Are efforts driven by AI and machine learning up to the task?
Reassessing the use of race in clinical algorithms
Race is often included as a biological construct in clinical guidance, but experts assert that its use must be reexamined to promote health equity.
Personalized medicine Biohealth Tech Hub awarded $49M
The Wisconsin Biohealth Tech Hub will use $49 million in federal funding to drive innovation, manufacturing and workforce development in the realm of precision medicine.
Insights
Insights is the research division of Xtelligent Healthcare Media. Our work aims to leverage Xtelligent’s diverse readership of healthcare professionals across various sectors of the industry to understand real-world challenges and identify effective solutions.
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Healthcare Strategies: A Podcast
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A podcast for healthcare professionals seeking solutions to today's and tomorrow's top challenges. Hosted by the editors of Xtelligent Healthcare Media, this podcast series focuses on real-world use cases that are leading to tangible improvements in care quality, outcomes, and cost.
Guests from leading provider, payer, government, and other organizations share their approaches to transforming healthcare in a meaningful and lasting way.
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Latest News
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Deep learning links lung shape differences and COVID-19 severity
A 3D residual convolutional network analysis revealed that COVID-19 patients experienced significant deformities to the mediastinal and basal surfaces of the lungs.
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Machine learning-driven liquid biopsy identifies lung cancer risk
A machine learning-based approach could flag individuals at high risk for lung cancer by analyzing DNA fragments found in blood, which may improve screening uptake.
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Deep brain stimulation atlas, AI may personalize Parkinson’s treatment
Using a newly developed symptom atlas, a deep brain stimulation algorithm could optimize personalized treatments for Parkinson’s disease.
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Machine learning tool accurately predicts spine surgery outcomes
A machine learning approach using wearable data, EHRs and ecological momentary assessment information outperformed existing spine surgery outcome prediction tools.
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Synthetic tumor data enhances training for cancer detection AI
An artificial intelligence model trained solely on synthetic liver tumor data performed on par with models trained using images of real tumors.
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Interpretable machine learning helps clinicians classify EEG anomalies
An interpretable machine learning model improved clinicians’ performance in reading electroencephalography charts, boosting accuracy from 47% to 71%.
Features
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Investigating electronic phenotyping’s role in clinical analytics
Electronic phenotyping has significant potential to drive EHR-based data mining and clinical research, but patient privacy remains a major concern.
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Weighing the pros and cons of synthetic healthcare data use
Synthetic data is touted as a privacy-preserving alternative to the use of real-world patient information in healthcare analytics.
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Exploring generative artificial intelligence in healthcare
As the hype around generative AI continues, healthcare stakeholders must balance the technology’s promise and pitfalls.
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WEDI Conf. looks at AI for ROI & interoperability
WEDI’s Spring Conference saw experts discussing best practices and emerging trends in artificial intelligence and health information exchange.