New & Notable
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.
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.
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.
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.
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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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%.
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South Carolina gains web-based tool for population health surveillance
Six new data dashboards will track cancer, care access and SDOH across South Carolina’s 46 counties in an effort to advance population health.
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NIH funds validation of graft-versus-host disease assessment AI
A $4.2 million grant will support the validation of an artificial intelligence tool to measure skin changes in patients with chronic graft-versus-host disease.
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Deloitte: healthcare consumers’ trust in generative AI has room to grow
Deloitte’s 2024 consumer healthcare survey found that adoption of GenAI for health reasons has progressed little in the last year due to consumers’ distrust.
Features
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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.
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Exploring the role of AI in healthcare risk stratification
Artificial intelligence is taking the healthcare industry by storm, and its applications in risk stratification have significant potential to improve outcomes.