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AI in Healthcare and Scienceβ€’β€’4 min readβ€’731 words

πŸ€– LLMs in Biomedical Applications - Drug Design

πŸ‘οΈ0reads (human + AI)πŸ€–0AI ingestions

πŸ€– LLMs in Biomedical Applications - Drug Design

This article discusses the successful application of large language models (LLMs) in biomedical tasks, specifically drug design, contradicting some assessments of current LLM capabilities. The research highlights the potential of adequately trained LLMs in this field.

Key Points:

β€’ LLMs can be effectively trained for complex biomedical tasks.

β€’ Adequate training enables LLMs to perform drug design functions.

β€’ This research challenges existing limitations perceptions of LLMs.

πŸ”— Resources:

β€’ Moremi Bio β†— - Research on LLM drug design

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πŸ’‘ Memorial Day Remembrance

This article is a brief message of remembrance for Memorial Day, honoring those who have lost their lives in military service.

Key Points:

β€’ Memorial Day is a day for remembrance and reflection.

β€’ It's important to acknowledge the sacrifices made by military personnel.

β€’ The day encourages pausing to honor those who have served.

πŸ”— Resources:

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πŸ’‘ Memorial Day Reflection

This message observes Memorial Day, remembering the sacrifices of military service members and highlighting their contribution to freedoms and innovation, even in healthcare and technology.

Key Points:

β€’ Memorial Day is a time for remembrance.

β€’ The sacrifices of military personnel enable freedoms and innovation.

β€’ Honoring their service is crucial.

πŸ”— Resources:

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πŸ€– AI in Healthcare - Addressing Patient Follow-up

This article discusses the high rate of patient loss to follow-up for lung nodules and introduces qTrack, an AI-powered solution designed to improve patient management and address this issue.

Key Points:

β€’ Over 70% of patients with lung nodules are lost to follow-up.

β€’ This highlights a critical need for improved patient management.

β€’ qTrack aims to streamline communication and close this gap.

πŸ”— Resources:

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✨ Award-Winning Medtech - OCT Technology and AI

This article announces an award win for PerimeterMed's S-Series OCT technology and its investigational AI-powered Next Gen system for breast cancer surgeries.

Key Points:

β€’ PerimeterMed won a 2025 TAG Award in the medtech category.

β€’ S-Series OCT technology visualizes tissue microstructures in real time.

β€’ Next Gen AI aims to improve breast cancer surgery.

πŸ”— Resources:

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πŸ€– AI in Gastric Cancer Diagnosis

This article discusses a study on using Ibex Gastric AI technology for the diagnosis of gastric cancer, highlighting the importance of accurate and timely diagnosis in improving treatment and survival rates.

Key Points:

β€’ Over a million new gastric cancer cases are diagnosed annually.

β€’ Accurate and timely diagnosis is crucial for effective treatment.

β€’ A study explores the use of Ibex Gastric AI in diagnosis.

πŸ”— Resources:

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πŸ’‘ Measles Outbreak in Texas - Vaccination Importance

This article highlights a measles outbreak in Texas, emphasizing the importance of timely immunization and the high number of unvaccinated individuals among those infected.

Key Points:

β€’ Over 720 measles cases reported in Texas.

β€’ Most infected individuals were unvaccinated.

β€’ Timely immunization is crucial to prevent outbreaks.

πŸ”— Resources:

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πŸ€– AI in Healthcare - Redefining Healthcare at London Tech Week

This article announces a presentation by Recursion's Chief Scientist on the topic of AI's role in redefining healthcare at London Tech Week.

Key Points:

β€’ Presentation on AI's role in redefining healthcare.

β€’ Discussion at London Tech Week.

β€’ Presented by Recursion's Chief Scientist.

πŸ”— Resources:

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πŸ€– Drug Discovery - High-Throughput Molecular Screening

This article reports on a significant milestone achieved by Metanova Labs in their drug discovery efforts, involving high-throughput screening of a large number of molecules against mammalian proteins.

Key Points:

β€’ Over 1.1 million molecules screened against nearly 3,000 proteins.

β€’ A major milestone in drug candidate identification.

β€’ Multi-parametric search across over 1 billion molecules.

πŸ”— Resources:

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πŸ€– Virtual Cells in Drug Discovery

This article discusses a new perspective paper outlining the vision for a virtual cell system in drug discovery, focusing on an iterative process of prediction, experimentation, and refinement.

Key Points:

β€’ New perspective paper on virtual cells in drug discovery.

β€’ Focus on iterative loop of prediction, experimentation, and refinement.

β€’ Aims to reliably drive the discovery of new drugs.

πŸ”— Resources:

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Drix10
Written by Drix10

Co founder @ PartPilot | 1 x Acquired Founder | Canopy @ f.inc | Cybersec @ DSU | 2x International Hackathon πŸ†. Read more on drix10.com.