Miyabe みやべ Shields, PhD’s Post

Check out the latest installment in the calibration science series! Here, Brian C. Smith, PhD, discusses variance, how to calculate the standard deviation of a data set, how to calculate the correlation coefficient, and more. ➡️ Read the Cannabis Analysis column from our latest issue: https://ow.ly/sMTB50SAttK

Check out the next installment in the calibration science series! Here, Brian C. Smith, Ph.D., discusses how to spot outliers and potential ways to correct them in data sets. ➡️ Read the Cannabis Analysis column from our latest issue here: https://ow.ly/CVF950Tn86e

✅Learn how experts at Impinj examined more than 70 published studies that back up RAIN’s eco-friendly claims with definitive data✅ Link below in the comments 👇

Explore our new biobank tool to streamline clinical profiling in human biospecimen collection. #Biobank #Biospecimen #Data #Bioscience

Citeline's Sheila Omondi and Jake Mathon lend their insights ― along with Trialtrove data ― to this PharmaVoice article on challenge trials. The article covers the number of active challenge trials, added logistical considerations, and the ethical implications of this research. https://ow.ly/cRzn30sAuxL #ChallengeTirals #ClinicalTrials #PharmaVoice

💥 Many pathways on a single poster. This is really impressive, although from 1993 and far from complete. Zoom in and look at the details! Maybe you have an even more complete or more recent overview? (Please share)

While it's hard to pick a favorite, this session on what it actually takes to turn piles of human data into actionable insights may be the one I'm most looking forward to for its methodological geekiness 🤓 Come join the conversation! At #BioCenturyGrandRounds, The Human Data Revolution Session will explore how to make these data troves fit for purpose: ➤ Methods-for-purpose: Analytical tools that parse signal from noise, without flattening complexity ➤ Data-for-purpose: Go big, go deep, or go long? Speakers in this session include: ➤ Gonçalo Abecasis, Regeneron ➤ Amy Abernethy, former FDA ➤ Daniel Burkhardt, Cellarity ➤ David B. Goldstein, Actio Biosciences, Inc. ➤ Colin Hill, Aitia ➤ Mathai Mammen, M.D., Ph.D., FogPharma ➤ Elizabeth Ann Stringer, NashBio ➤ And more... Download the conference brochure to view the full agenda: https://loom.ly/TGB3Mmk Register: https://loom.ly/xUy6IGo #biomedicaldata #diseasetargets #markers #humandata

🧠 Since May is Mental Health Awareness Month, I asked ChatGPT, "How can AI help with mental health issues?" I had some reservations about AI-powered chatbots and virtual therapists, but the final paragraph put my mind at ease. Here's a summary of how ChatGPT thinks AI can make a difference in mental health care: 💡 Early Detection and Diagnosis: AI algorithms can analyze medical records, speech patterns, and even social media to spot early signs of mental health disorders. This could mean earlier detection of conditions like depression and anxiety. 💡 Chatbots and Virtual Therapists: These AI-powered platforms offer a safe space for people to discuss their feelings. They can guide users through basic cognitive behavioral therapy (CBT) exercises and even flag when human intervention is needed. 💡 Remote Monitoring and Telehealth: AI tools can remotely monitor patients, alerting healthcare professionals to changes in behavior or mood, especially useful for those with limited access to in-person care. 💡 Personalized Treatment Plans: By analyzing patient history and treatment responses, AI can help create personalized treatment plans, leading to more effective care. 💡 Predictive Analytics for Risk Assessment: AI can identify patterns that indicate a risk of mental health crises, allowing for proactive intervention. 💡 Resource Allocation and Management: AI can optimize the distribution of mental health resources, ensuring that patients get care when and where they need it most. 💡 Research and Insights: AI can sift through vast amounts of medical research, uncovering new insights and best practices to inform treatment. 💡 Language Translation and Accessibility: AI can translate languages, making mental health resources more accessible to non-English speakers. 💡 Support for Caregivers and Families: AI-based tools can guide caregivers and families on how to best support loved ones with mental health issues. 💡 Education and Awareness: AI can help create educational campaigns to raise awareness about mental health issues and reduce stigma. 🌟 While AI offers significant benefits in mental health care, it's crucial to consider limitations and ethical concerns, including privacy and the need for a human touch. By blending AI with traditional mental health practices and involving professionals at every stage, we can maximize AI's positive impact in this critical field. #MentalHealthAwarenessMonth #AIinMentalHealth #HealthcareTech #Citeline #AI

The perception of cannabis and mushrooms is critically limited by outdated stigmas—focusing only on THC's "high" or mushrooms' psychedelic effects. This is like saying a book is only good for its cover art. In my latest episode, George Moulton, Co-Founder & CEO of Fun Guy, discusses the broader potential of these natural substances. From medical benefits to the inspiration behind his company, George offers a fresh perspective on their future. Give it a listen and let me know what you think. https://lnkd.in/eg5jZCag

We are not guided by expectations or beliefs in conducting our science. What we do focus on is data. In other words, reliable and methodologically acquired information based on facts. Here ➡️ https://lnkd.in/eDyf-faX , facts on our leading heated tobacco product speak for themselves. #HardData #ScientificMethod #ScientificConclusion #ScienceInformation