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Author of Unlocking Women's Health, FemTech & the Quest for Gender Equity - Global Women's Health Leader - Founder FemHealth Insights, Host of FemTech Focus Podcast - Scientist - Investor - Speaker - Consultant
Join us live on 3rd December at 1 p.m EST as we dive into AI in Women’s Health with Jaycee Kaufman, Research Scientist at Klick and Alfred Whitehead, EVP Applied Sciences at Klick.
In this session, hosted by Dr. Brittany Barretto, we will be exploring:
- The role AI will play in bridging gaps in the current healthcare system
- Companies paving the way in adopting AI to advance women’s health
- Theraputic and speciality based applications of AI in FemTech
- Adopting AI as a part of a FemTech product roadmap
About the speakers
Jaycee is a Research Scientist at Klick. Her focus is using computational techniques to analyze physiological signals for improved understanding and prediction of health and disease. She has an impressive portfolio of patents on her research in digital biomarkers and regularly publishes peer-reviewed articles in scientific journals on topics related to digital health, biomedical engineering, data science, and artificial intelligence.
Alfred is the EVP Applied Sciences at Klick Consulting and Klick Labs. He is a leader in healthcare innovation, combining his scientific expertise as a published astrophysicist, with his technical leadership and entrepreneurial spirit. He leads innovation and product design consultancy within the healthcare and life sciences space at Klick.
𝗛𝗼𝘄 𝗰𝗮𝗻 𝘄𝗲 𝗮𝗰𝗰𝗲𝗹𝗲𝗿𝗮𝘁𝗲 𝘁𝗵𝗲 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝗼𝗳 𝗻𝗲𝘄 𝗺𝗲𝗱𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝗮𝗻𝗱 𝗿𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝗶𝘇𝗲 𝗵𝗲𝗮𝗹𝘁𝗵𝗰𝗮𝗿𝗲?
#AI and supercomputing technologies are enabling entirely new approaches to science and research.
At EuroCC Austria's webinar, leading life sciences professionals will guide you through the landscape of AI tools in structural biology, focusing on the groundbreaking AlphaFold.
You'll get the opportunity to discuss the role of AI in personalized medical therapies and explore the contribution of supercomputers in this field.
One of the Speakers is Barbara Sladek.
Barbara is co-founder of Biome Diagnostics.
She will offer valuable insights into the gut microbiome,
sharing the latest scientific discoveries and shedding light on how the company utilizes data to decode its secrets.
The human intestinal microbiome consists of a dynamic multispecies community of trillions of bacteria. Identifying the multitude of pathways in which the symbiotic microbiome interacts with the human body is hence an exceedingly complex undertaking.
Only with the power of AI and advanced bioinformatic algorithms are we able to decipher the secrets of the intestinal microbiome and use these insights for medical purposes.
Barbara Sladek will present the newest research in this area and the potential it holds for doctors and patients.
Register for EuroCC’s webinar and get answers to some of the most captivating questions in the domain of life sciences!
https://lnkd.in/emGCnqWr
Founder/President of BiomedConnect| Harvard ALP Alumni || COBUBA President| || Interim President of Biomedical sciences students association of Zambia || Ambassador for Acquah Health Foundation UK
Exciting News, *BiomedConnect* Family!
Join our upcoming panel discussion on "THE INVOLVEMENT OF *ARTIFICIAL* *INTELLIGENCE* IN HELPING STUDENTS/PROFESSIONALS IN SCIENCE"! Discover how AI is reshaping science and medicine.
🎤 Our expert panelists will explore AI's impact on learning experiences, research, and patient care in biomedical sciences.
Have burning questions? You'll have the chance to ask directly during the session!
Whether you're a student or a seasoned professional, this event is for you! Date: *Thursday* 7th of March at *8PM* (*CAT*) and *7PM* (*WAT*).
🔗 Join our Telegram channel: https://lnkd.in/dAYV3Hyi
Don't miss out on this opportunity to expand your knowledge and network with fellow enthusiasts. Let's unlock the potential of AI together!
See you there!
Regards,
Cc: BiomedConnect executive
Cc: BiomedConnect Ambassadors
#BiomedConnect#ConnectingMindsAdvancingHealth
#Cancer#patients undergoing #Radiotherapy shift, move, swallow, digest, pass gas, settle, and breathe over the course of treatment #delivery. These movements change the actual location of the #tumor being treated compared to what is expected, risking either under-treating the tumor or over-radiating the surrounding, healthy tissue.
Techniques like respiratory gating and new technologies such as #MRI-guided radiation therapy improve the effectiveness of tumor tracking and minimize the impact of both small and large body movements on the delivery of radiation. They achieve this largely by not delivering radiation when the target is not in its expected position.
Unfortunately, this has the effect of making treatments last longer, which is both an inconvenience to the patient and a limit on the number of patients who can be treated per day on a given linear accelerator.
This approach is somewhat different from techniques associated with what we normally call #adaptive#radiotherapy, where physicians address changes that take place in the body over a longer period, such as changes in tumor size or shape, or the patient's hydration level or weight that often accompany both disease and treatment. In adaptive radiotherapy, a patient is scanned before each treatment, and the plan is potentially adjusted based on these macro changes to each patient's individual #physiology.
The "holy grail" of introducing massively increased computational power and #machine#learning would be to combine both of these techniques into a unified approach, allowing #AI-enhanced software controlling the accelerator to adapt in real-time to actual and predictive movement. This would enable targeting tumors more precisely, at higher doses, over less time, and with lower collateral damage to adjacent structures.
The safety protocols and guardrails around allowing machines more #autonomy in adapting plans and their #constraints to the delivery of real-time therapy are almost inconceivably perilous and equally complex.
One thing is certain: the technology will get there before we are ready for it, and that means the time for these conversations is now.
It requires a lot of infrastructure and logistics to build complex AI systems. Today we’re sharing an initial set of cell models in a centralized place to accelerate gains from machine learning in cell biology. This includes scGenePT and SubCell, models built and supported by CZI and our collaborators. They come with ready-to-run notebooks, access to both the code and processed data to train and validate new models, in support of open science at the interface of AI and bio. It’s exciting to support our mission to integrate AI into biomedical research, where this hard work will transform possibilities into real scientific breakthroughs.
https://lnkd.in/gqaiGHyR
We're excited to share a new publication that highlights the establishment and journey of the Stanford Center for Artificial Intelligence in Medicine and Imaging (AIMI Center) over the past six years. Published in Mayo Clinic Proceedings: Digital Health, the paper details how we created an interdisciplinary center to address clinically significant questions with AI/ML, fostering collaboration among clinicians, data scientists, and computer scientists to tackle complex biomedical challenges.
The publication outlines four core pillars that have guided our efforts:
- Building a vibrant interdisciplinary community
- Catalyzing extramural funding through internal grant programs
- Developing infrastructure to enable large-scale, AI-ready clinical datasets
- Engaging and educating the broader research community
It also reflects on lessons learned and previews what's ahead as we continue to advance the role of AI in healthcare.
We invite you to read the full text and learn more about our center's journey: https://bit.ly/4hZr92h
We are deeply grateful to the broader AI in health and medicine community for your support and partnership in transforming medicine with AI. Special thanks to everyone who has contributed to this journey, especially: Curtis Langlotz, Johanna Kim, Nigam Shah, Matthew Lungren MD MPH, David Larson, Somalee Datta, Fei-Fei Li, Ruth O Hara, Thomas Montine, Robert A. Harrington, Garry Gold, Stanford Radiology, Stanford University School of Medicine, Stanford Department of Medicine, Stanford Medicine: Department of Pathology#StanfordAIMI#AIinHealthcare#HealthTech#FutureOfMedicine#ResponsibleAI
It requires a lot of infrastructure and logistics to build complex AI systems. Today we’re sharing an initial set of cell models in a centralized place to accelerate gains from machine learning in cell biology. This includes scGenePT and SubCell, models built and supported by CZI and our collaborators. They come with ready-to-run notebooks, access to both the code and processed data to train and validate new models, in support of open science at the interface of AI and bio. It’s exciting to support our mission to integrate AI into biomedical research, where this hard work will transform possibilities into real scientific breakthroughs.
https://lnkd.in/gqaiGHyR
When AI, cell biology, and open science converge, we unlock groundbreaking possibilities! Proud to be part of this journey and excited to see the launch of virtual cell models by #cziscience--paving the way for transformative insights in biomedical research.
🚀 #OpenScience#VirtualCellModels#AIInBiology"
It requires a lot of infrastructure and logistics to build complex AI systems. Today we’re sharing an initial set of cell models in a centralized place to accelerate gains from machine learning in cell biology. This includes scGenePT and SubCell, models built and supported by CZI and our collaborators. They come with ready-to-run notebooks, access to both the code and processed data to train and validate new models, in support of open science at the interface of AI and bio. It’s exciting to support our mission to integrate AI into biomedical research, where this hard work will transform possibilities into real scientific breakthroughs.
https://lnkd.in/gqaiGHyR
Cells are the smallest units of life, and despite all the scientific research done to date, there’s still so much we don’t know about them—especially how they change when we get sick. That’s why we’re building AI-powered virtual cells to help scientists explore the behavior of healthy and diseased cells and better understand human health.
But how do we get there? Read more about how the scientific community can move forward in creating the future of AI-powered biomedical research:
