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Advancing pediatric cancer predictions through generative artificial intelligence and machine learning

Yadav et al. | Dec 21, 2024

Advancing pediatric cancer predictions through generative artificial intelligence and machine learning

Pediatric cancers pose unique challenges due to their rarity and distinct biological factors, emphasizing the need for accurate survival prediction to guide treatment. This study integrated generative AI and machine learning, including synthetic data, to analyze 9,184 pediatric cancer patients, identifying age at diagnosis, cancer types, and anatomical sites as significant survival predictors. The findings highlight the potential of AI-driven approaches to improve survival prediction and inform personalized treatment strategies, with broader implications for innovative healthcare applications.

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Using Artificial Intelligence to Forecast Continuous Glucose Monitor(CGM) readings for Type One Diabetes

Jalla et al. | Aug 07, 2024

Using Artificial Intelligence to Forecast Continuous Glucose Monitor(CGM) readings for Type One Diabetes
Image credit: The authors

People with Type One diabetes often rely on Continuous Blood Glucose Monitors (CGMs) to track their blood glucose and manage their condition. Researchers are now working to help people with Type One diabetes more easily monitor their health by developing models that will future blood glucose levels based on CGM readings. Jalla and Ghanta tackle this issue by exploring the use of AI models to forecast blood glucose levels with CGM data.

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Examining the correlation between Massa Medicata Fermentata and Crohn’s disease: Implications for treatment and patient safety

Wang et al. | Sep 15, 2025

Examining the correlation between Massa Medicata Fermentata and Crohn’s disease: Implications for treatment and patient safety

Crohn’s disease is a chronic inflammatory bowel condition with symptoms like abdominal pain, fatigue, diarrhea, and malnutrition. Though there's no cure, various treatments help manage it. This study explored the potential impact of Massa Medicata Fermentata (MMF), a fermented Chinese herbal medicine containing Saccharomyces cerevisiae, on Crohn’s disease.

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Investigating the Role of Biotic Factors in Host Responses to Rhizobia in the System Medicago truncatula

Rathod et al. | Jan 22, 2019

Investigating the Role of Biotic Factors in Host Responses to Rhizobia in the System Medicago truncatula

Nitrogen-fixing bacteria, such as the legume mutualist rhizobia, convert atmospheric nitrogen into a form that is usable by living organisms. Leguminous plants, like the model species Medicago truncatula, directly benefit from this process by forming a symbiotic relationship with rhizobia. Here, Rathod and Rowe investigate how M. truncatula responds to non-rhizobial bacterial partners.

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Albuterol extends lifespan of Caenorhabditis elegans

Belkin et al. | Oct 19, 2021

Albuterol extends lifespan of <i>Caenorhabditis elegans</i>

The objective of this experiment is to determine if the medication albuterol has a positive impact on the lifespan of C. elegans. We hypothesize that if albuterol is added to the diet of C. elegans, then the lifespan of C. elegans will increase. Albuterol increased the mean lifespan of C. elegans by 4.31 ± 0.13 days, compared to the control group and increased the outer range of the C. elegans lifespan. The method of which this occurred is still unknown.

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Antibacterial activity by Dombeya wallichii plant extracts obtained by ultrasound-assisted extraction

Herur et al. | Nov 13, 2023

Antibacterial activity by <em>Dombeya wallichii</em> plant extracts obtained by ultrasound-assisted extraction

Medicinal plants could be a good source of medication to combat antibiotic resistance. Dombeya wallichii, which is commonly called Pink Ball Tree in the family Sterculiaceae, has been documented to have medicinal potential. We observed the highest antibacterial activity in the stem extracts, followed by leaf and bark extracts. The extracts were more effective against tested Gram-positive bacteria when compared with Gram-negative strains.

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