Morris Misel’s Post

💡"...Only around one in three adults in the US completes any kind of advance directive—a legal document that specifies the end-of-life care they might want to receive. Wendler estimates that over 90% of end-of-life decisions end up being made by someone other than the patient..." 💡"...Some surrogates experience “decisional paralysis” and might opt to use the tool to help steer them through a decision-making process, says Kaplan. In cases like these, the P4 could help ease some of the burden surrogates might be experiencing, without necessarily giving them a black-and-white answer..." 💡 "...The team proposes using AI and machine learning to predict a patient’s treatment preferences on the basis of personal data such as medical history, along with emails, personal messages, web browsing history, social media posts, or even Facebook likes. The result would be a “digital psychological twin” of a person—a tool that doctors and family members could consult to guide a person’s medical care..."

The problem with using AI in maternal healthcare is that the technology is often designed without patients of color in mind. Here’s how to change that.

This morning, Roy Jakobs, CEO of Royal Philips appeared on CNBC to discuss the transformative role of AI in healthcare. Jakobs specifically mentioned their collaboration with Nicklaus Children's, emphasizing how they are using technology to enhance the experience for children undergoing medical scans. With the help of AI, Philips is reducing scan times and improving the quality of outcomes and readings. These advancements not only streamline processes but also create a more comforting and efficient environment for our young patients. Watch the full interview here: https://lnkd.in/egtYUafm #healthcare #nicklauschildrens #pediatrics #AI #healthcareinnovation

We are delighted to announce our latest opinion article in Frontiers in Global Women’s Health titled, “The Impact of Informant-Related Characteristics Including Sex/Gender on Assessment of Alzheimer’s Disease Symptoms and Severity.”   Did you know that the Clinical Dementia Rating Scale (CDR) is pivotal in Alzheimer’s disease (AD) staging?   Have you ever wonder which is the impact of the gender of caregiver characteristics on its readout?   Here we discussed how this factor —often overlooked—play a crucial role in the accuracy of this assessment.   Key Takeaways on possible biases:   Dynamics: The informant’s relationship with the patient can significantly affect the perception of the patient’s health status, potentially influencing severity scores.   Sex/Gender Influence: The sex/gender of the informant can also influence dementia assessments in significant ways.   Cultural Lens: Cultural and socioeconomic characteristics can influence how caregivers assess AD symptoms and severity.   These factors are vital in understanding caregiver reports and ensuring precise patient diagnosis and staging, especially when used as primary endpoints in clinical trials.   A heartfelt thank you to the brilliant minds behind this work: Ella Abken, Laura Castro, Antonella, Maria Teresa Ferretti, and Carmela Tartaglia for their invaluable collaboration. 👏   #AlzheimersResearch #WomensBrainHealth #NeurodegenerativeDiseases #ClinicalDementiaRating #HealthcareInnovationbias Link to the publication: https://lnkd.in/eUteA-u4   🤝 Donate today to support the advancement of brain and mental health: https://lnkd.in/epBrMRP5

Unlocking ROI: How AI Boosted Patient Engagement Discover how a fertility healthcare center transformed their patient acquisition by integrating AI. With over 200 new scheduled consultations in just one year, we explore the impact of AI on user engagement and ROI in the healthcare industry. #HealthcareInnovation #AIBenefits #PatientEngagement #ROIStrategy #DigitalTransformation #FertilityCare #MedicalAI #PatientAcquisition #HealthcareMarketing #TechInHealthcare

AI is already transforming healthcare, but when it comes to maternal care, we must ask: How can we prevent AI bias from worsening existing disparities? The U.S. has one of the highest maternal mortality rates among developed countries, particularly affecting Black women and underserved populations. While AI has the potential to revolutionize care, ensuring algorithms are built without bias is key. From diverse data sets to transparent oversight, we must prioritize fairness in these technologies to ensure they benefit all women equally. #maternalhealth #ai Post research credit: Reva Sanders https://lnkd.in/gC7Z_Bqu

The reporting in MIT Technology Review is such a mixed bag. Some good critical work, some "look shiny!" tech reporting that at best quotes a few "skeptics" towards the bottom before returning to boosterism. This one is an example of that -- a longish post (was a short thread on other platforms): https://lnkd.in/gwntDZnJ This is the same horrific idea that I wrote about in my MAIHT3k newsletter post on Monday, but @techreview goes for the "ooh shiny!" angle instead: https://lnkd.in/g8usVEtA There is so much awfulness in this article that's just matter-of-factly platformed rather than contextualized. A few examples: "Over 10 years ago, he developed the idea for a tool that would predict a patient’s preferences on the basis of characteristics such as age, gender, and insurance status. That tool would have been based on a computer algorithm trained on survey results from the general population." "Instead of being based on crude characteristics, the new tool the researchers plan to build will be personalized. The team proposes using AI and machine learning to predict a patient’s treatment preferences on the basis of personal data such as medical history, along with emails, personal messages, web browsing history, social media posts, or even Facebook likes. The result would be a “digital psychological twin” of a person—a tool that doctors and family members could consult to guide a person’s medical care." "In such cases, it might be difficult to find the person’s social media profile, for example. But other information might prove useful. “If something turns out to be a predictor, I would want it in the model,” says Wendler. “If it turns out that people’s hair color or where they went to elementary school or the first letter of their last name turns out to [predict a person’s wishes], then I’d want to add them in.”" And *of course* the article has to end with this tired trope: "On the other hand, humans are fallible, too. Vasiliki Rahimzadeh, a bioethicist at Baylor College of Medicine, thinks the P4 is a good idea, provided it is rigorously tested. “We shouldn’t hold these technologies to a higher standard than we hold ourselves,” she says." If you're thinking about this as an "accuracy" problem, you've already lost the plot ... as well illustrated by this quote from one of the dissenting voices hidden in the middle of the article: "Moore is a clinical ethicist who offers consultations for patients, family members, and hospital staff at two hospitals. “So much of our work is really just sitting with people who are facing terrible decisions … they have no good options,” she says. “What surrogates really need is just for you to sit with them and hear their story and support them through active listening and validating [their] role … I don’t know how much of a need there is for something like this, to be honest.”"

One of my favorite things about fall is ASRM, learning about new initiatives, ideas, and innovations in the fertility space, and connecting with friends from all over the world! One of the big topics over the last year increasingly has been the usage of AI in the fertility clinic setting. However... I believe that not enough attention has been paid to the usage of AI BEFORE patients walk in the door...using it to educate new patients, nurture them in to becoming patients in your clinic and guiding them through the process. That's what I am focused on Cima, to help bring to together the pre clinic AI process and the clinic based AI processes. I'd love to connect with you at ASRM and talk about how this can be perfectly deployed in your clinic and practice setting! . . #asrm #fertility #asrm #marketing

One of my favorite things about fall is ASRM, learning about new initiatives, ideas, and innovations in the fertility space, and connecting with friends from all over the world! One of the big topics over the last year increasingly has been the usage of AI in the fertility clinic setting. However... I believe that not enough attention has been paid to the usage of AI BEFORE patients walk in the door...using it to educate new patients, nurture them in to becoming patients in your clinic and guiding them through the process. That's what I am focused on Cima, to help bring to together the pre clinic AI process and the clinic based AI processes. I'd love to connect with you at ASRM and talk about how this can be perfectly deployed in your clinic and practice setting! . . #asrm #fertility #asrm #marketing