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jcmarchi · 1 month

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Student spotlight: Victory Yinka-Banjo

New Post has been published on https://thedigitalinsider.com/student-spotlight-victory-yinka-banjo/

Student spotlight: Victory Yinka-Banjo

This interview is part of a series from the MIT Department of Electrical Engineering and Computer Science featuring students answering questions about themselves and life at the Institute. Today’s interviewee, Victory Yinka-Banjo, is a junior majoring in MIT Course 6-7: Computer Science and Molecular Biology. Yinka-Banjo keeps a packed schedule: She is a member of the Office of Minority Education (OME) Laureates and Leaders program; a 2024 fellow in the public service-oriented BCAP program; has previously served as secretary of the African Students’ Association, and is now undergraduate president of the MIT Biotech Group; additionally, she is a SuperUROP Scholar; a member of the Ginkgo Bioworks’ Cultivate Fellowship (a program that supports students interested in synthetic biology/biotech); and an ambassador for Leadership Brainery, which equips juniors/leaders of color with the resources needed to prepare for graduate school. She recently found time to share a peek into her MIT experience.

Q: What’s your favorite building or room within MIT?

A: It has to be the Broad Institute of MIT and Harvard on Ames Street in Kendall Square, where I do my SuperUROP research in Caroline Uhler’s lab. Outside of classes, you’re 90 percent likely to find me on the newest mezzanine floor (between the 11th and 12th floor), in one of the UROP [Undergraduate Research Opportunities Program] rooms I share with two other undergrads in the lab. We have standing desks, an amazing coffee/hot chocolate machine, external personal monitors, comfortable sofas — everything, really! Not only is it my favorite building, it is also my favorite study spot on campus. In fact, I am there so often that when friends recently planned a birthday surprise for me, they told me they were considering having it at the Broad, since they could count on me being there.

I think the most beautiful thing about this building, apart from the beautiful view of Cambridge we get from being on one of the highest floors, is that when I was applying to MIT from high school, I had fantasized working at the Broad because of the groundbreaking research. To think that it is now a reality makes me appreciate every minute I spend on my floor, whether I am doing actual research or some last-minute studying for a midterm.

Q: Tell me about one interest or hobby you’ve discovered since you came to MIT.

A: I have become pretty involved in the performing arts since I got to MIT! I have acted in two plays run by the Black Theater Guild, which was revived during my freshman year by one of my friends. I played a supporting role in the first play called “Nkrumah’s Last Day,” which was about Ghana at a time of governance under Kwame Nkrumah, its first president. In the second play, a ghost story/comedy called “Shooting the Sheriff,” I played one of the lead roles. Both caused me to step way out of my comfort zone and I loved the experiences because of that. I also got to act with some of my close friends who were first-time stage actors as well, so that made it even more fun.

Outside of acting, I also do spoken word/poetry. I have performed at events like the African Students Association Cultural Night, MIT Africa Innovate Conference, and Black Women’s Alliance Banquet. I try to use my pieces to share my experiences both within and beyond MIT, offering the perspective of an international Nigerian student. My favorite piece was called “Code Switch,” and I used concepts from [computer science] and biology (especially genetic code switching), to draw parallels with linguistic code-switching, and emphasize the beauty and originality of authenticity. This semester, I’m also a part of MIT Monologues and will be performing a piece called “Inheritance,” about the beauty of self-love found in affection transferred from a mother.

Q: Are you a re-reader or a re-watcher — and if so, what are your comfort books, shows, or movies?

A: I don’t watch too many movies, although I used to be obsessed with all parts of “High School Musical;” and the only book I’ve ever reread is “Americanah.” I would actually say I am a re-podcaster! My go-to comfort-podcast is this episode, “A Breakthrough Unfolds”, by Google DeepMind. It makes me a little emotional every time I listen. It is such an exemplification of the power of science and its ability to break boundaries that humans formerly thought impossible. As a computer science and biology major, I am particularly interested in these two disciplines’ applications to relevant problems, like the protein-folding problem discussed in the episode, which DeepMind’s solution for has caused massive advances in the biotech industry. It makes me so hopeful for the future of biology, and the ways in which computation can advance human health and precision medicine.

Q: Who’s your favorite artist?

A: When I think of the word ‘artist,’ I think of music artists first. There are so many who I love; my favorites also evolve over time. I’m Christian, so I listen to a lot of gospel music. I’m also Nigerian so I listen to a lot of Afrobeats. Since last summer, I’ve been obsessed with Limoblaze, who fuses both gospel and Afrobeats music! KB, a super talented gospel rapper, is also somewhat tied in ranking with Limo for me right now. His songs are probably ~50 percent of my workout playlist.

Q: It’s time to get on the shuttle to the first Mars colony, and you can only bring one personal item. What are you going to bring?

A: Oooh, this is a tough one, but it has to be my Brass Rat. Ever since I got mine at the end of sophomore year, it’s been nearly impossible for me to take it off. If there’s ever a time I forget to wear it, my finger feels off for the entire day.

Q: Tell me about one conversation that changed the trajectory of your life.

A: Two specific career-defining moments come to mind. They aren’t quite conversations, but they are talks/lectures that I was deeply inspired by. The first was towards the end of high school when I watched this TEDx Talk about storing data in DNA. At the time, I was getting ready to apply to colleges and I knew that biology and computer science were two things I really liked, but I didn’t really understand the possibilities that could be birthed from them coming together as an interdisciplinary field. The TEDx talk was my eureka moment for computational biology.

The second moment was in my junior fall during an introductory lecture to “Lab Fundamentals for Bioengineering,” by Professor Jacquin Niles. I started the school year with a lot of confusion about my future post-grad, and the relevance of my planned career path to the communities that I care about. Basically, I was unsure about how computational biology fit into the context of Nigeria’s problems, especially because my interest in the field is oriented towards molecular biology/medicine, not necessarily public health.

In the U.S., most research focuses on diseases like cancer and Alzheimer’s, which, while important, are not the most pressing health conditions in tropical regions like Nigeria. When Professor Niles told us about his lab’s dedication to malaria research from a molecular biology standpoint, it was yet another eureka moment. Like, Yes! Computation and molecular biology can indeed mitigate diseases that affect developing nations like Nigeria — diseases that are understudied, and whose research is underfunded.

Since his talk, I found a renewed sense of purpose. Grad school isn’t the end goal. Using my skills to shine a light on the issues affecting my people that deserve far more attention is the goal. I’m so excited to see how I will use computational biology to possibly create the next cure to a commonly neglected tropical disease, or accelerate the diagnosis of one. Whatever it may be, I know that it will be close to home, eventually.

Q: What are you looking forward to about life after graduation? What do you think you’ll miss about MIT?

A: Thinking about graduating actually makes me sad. I’ve grown to love MIT. The biggest thing I’ll miss, though, is Independent Activities Period (IAP). It is such a unique part of the MIT experience. I’ve done a web development class/competition, research, a data science challenge, a molecular bio crash course, and a deep learning crash course over the past three IAPs. It is such an amazing time to try something low stakes, forget about grades, explore Boston, build a robot, travel abroad, do less, go slower, really rejuvenate before the spring, and embrace MIT’s motto of “mind and hand” by just being creative and explorative. It is such an exemplification of what it means to go here, and I can’t imagine it being the same anywhere else.

That said, I look forward to graduating so I can do more research. My hours spent at the Broad thinking about my UROP are always the quickest hours of my week. I love the rabbit holes my research allows me to explore, and I hope that I find those over and over again as I apply and hopefully get into PhD programs. I look forward to exploring a new city after I graduate, too. I wouldn’t mind staying in Cambridge/Boston. I love it here. But I would welcome a chance to be somewhere new and embrace all the people and unique experiences it has to offer.

I also hope to work on more passion projects post-grad. I feel like I have this idea in my head that once I graduate from MIT, I’ll have so much more time on my hands (we’ll see how that goes). I hope that I can use that time to work on education projects in Nigeria, which is a space I care a lot about. Generally, I want to make service more integrated in my lifestyle. I hope that post-graduation, I can prioritize doing that even more: making it a norm to lift others as I continue to climb.

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iscariotapologist · 1 year

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brother is presently at a conference

#this is so depressing ☠️#what i wouldn't give to hang out with some non adventist religious scholars #its actually his wife doing the conference hes just there. and he let our mother come and she didnt tell him that her piece of shit #fake husband fucking just invited himself and they argued so much that they left... surprised they came anyway since this was a conference #for professional academics and they are uneducated insane people who live in a cult they claim cures cancer......lmao #me #ex sda

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figtreeandvine · 5 months

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I want to write a movie that is sort of the flip side of a Hallmark holiday movie. Not an anti-Hallmark movie, just like the other side of the same coin.

It starts with a well-dressed professional woman driving a convertible along a country road, autumn foliage in the background, terribly scenic. She turns onto a dirt road/long driveway, and stops next to a field of Christmas trees, all growing in neat, ordered rows, perfectly trimmed and pruned to form. She steps out of the car--no, she's not wearing high-heels, give her some sense!--and knocks on the door of a worn but nice-looking farmhouse. An older woman, late fifties maybe, answers the door, looking a bit puzzled. The younger woman asks if she can buy a Christmas tree now, today. The older woman says they don't do retail sales--and the younger woman breaks down crying.

Cut to the two women sitting at the kitchen table with cups of tea. The young woman (Michelle), no longer actively crying, explains that her mother loves Christmas more than anything, but is in the hospital with end-stage cancer. Her doctors don't think she'll live to see December, let alone Christmas. Nobody is selling Christmas trees in September, so could the older woman please make an exception, just this once? The older woman (Helen) regretfully explains that they have a contract to sell their trees that forbids outside sales. The younger woman nods, starts to stand up, but the older woman stops her with a hand and asks her what hospital her mother is in. After she answers the older woman says that "my Joe" will deliver a tree the next day. "Contract says I can't sell you a tree, but nothing says I can't give you one."

Next day "Joe" shows up at the hospital in flannel and jeans, with a smallish tree over her shoulder. Oh, whoops, that's Jo, Helen's daughter, short for Joanna, not Joe. Jo sets up the tree and even pulls out a box of lights and ornaments. Mother watches from hospital bed with a big smile as Jo and Michelle decorate the tree. Cue "end of movie" type sappiness as nurses and other patients gather in the doorway, smiling at the tree.

Cut to Michelle sitting in her dark apartment, clutching a mug of tea, staring out at the falling snow and the Christmas lights outside. Her apartment has no tree, no decorations, nothing. She starts at a knock on the door, goes to open it. Jo is standing there, again holding a tree over her shoulder.

Plot develops: the second tree is a gift, because Michelle might as well get it as the bank. The contract for the tree sales was an /option/ contract, which prevents them from selling to anyone else, but doesn't guarantee the sale. The corporation with the option isn't going to buy the trees, but Helen and Jo can't sell them anywhere else, and basically they get nothing. They'll lose the farm without the year's income. Michelle asks to see the contract and Jo promises to email it to her.

Next day at a very upscale law firm, Michelle asks at the end of a staff meeting if anyone in contract law still needs pro bono hours for the year. No one does, but a senior partner (Abe) takes her to his office and asks about it. She says the contract looks hinky to her ("Is that a legal term?" "Yes.") but contract law's not her thing. He raises an eyebrow and she grins and pulls a sheaf of paper out of her bag and hands it over. He reads it over, then looks up at her. "They signed this?"

More plot develops. Abe calls in underlings--interns, paralegals, whatever--and the contract is examined, dissected, and ultimately shredded (metaphorically). It's worse even than it looks--on January 1st Helen and Jo will have to repay the advanced they received at signing. The corporation has bought up a suspicious number of Christmas tree farms in previous years after foreclosure, etc.

Cut to Abe explaining all this to Helen and Jo while sitting with them and Michelle in a very swanky conference room. The firm is willing to take on the case pro bono, hopefully as a class's action suit for other farmers trapped by the contract--but there's no way it can go to court before January. Which will be too late to save the farm's income for the year. They might get enough in damages to tide them over, but….

After Michelle sees Helen and Jo out, she comes back and asks Abe if there's anything they can do immediately. Abe looks thoughtful for a long moment, then gets a really shark-like grin on his face. "Maybe…."

Cut to Helen wearing a bathrobe, coming into her kitchen in the morning. She looks out the window…and there's a food truck stopped in her driveway. She pulls a coat on over her robe and goes out--two more trucks have pulled up while she does this. Driver of the first truck asks her where they park. Another truck pulls up behind the others. Behind that is a black BMW--Abe rolls down the window and waves. Helen directs the trucks to the empty field/yard next to the house. Abe pulls up next to Helen's car and Jo's truck and parks. He and Michelle get out--Abe wearing a total power suit, Michelle in weekend casual.

The case will be easier if the corporation initially sues them for violating the (uninforcible!) contract, rather than them suing to corporation (damn if I know, but it's movie logic). So they're going to sell the trees now, and rounded up some food trucks and whatnot to draw people in.

Cue montage of Jo and Michelle running around helping people set up while Abe and Helen watch from the kitchen table. The table starts out covered in file folders…and slowly gains coffee cups and plates of cinnamon rolls. It becomes increasingly clear here that Abe and Helen are becoming as close as Jo and Michelle.

Everything gets set up and a very urban, very motley crowd appears--tats and studs and multiracial couples and LGBTQ parents and everything--and everyone is having a wonderful time eating funnel cake and choosing their tree so Jo and a bunch of rainbow-haired elves can cut it for them. At which point someone shows up from the corporation (maybe with a sheriff's deputy?) and starts yelling at Helen, who's running checkout. And suddenly Abe appears from the house and you realize why he's wearing that suit on a Saturday….

Cue confrontation and corporate flunky running off with their tail between their legs, blustering about suing. Cue Jo kissing Michelle. Cue Helen walking over and putting a hand on Abe's shoulder and smiling at her.

I want the lawyers to be the heroes because they are lawyers and know the law. I want a lesbian who lives in the country with her mother. I want urbanites to turn out as a community to help someone who isn't even part of their community. I want Michelle to keep working at her high-power job, loving Christmas and grieving her mother.

#hallmark #anti-hallmark #movie plot

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marcorossi · 1 month

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now i just feel bad for washington state

#first tournament in 22 years…pg had cancer…conference dead and u couldn’t find a life vest

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pathologylab · 20 days

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Exciting Day 1 at #AACR2024! Here's a sneak peek of the inspiring discussions from the #American Association for Cancer Research.

Huge thanks to all the scientists and doctors who stopped by #G2M's booth #853 as our team had insightful conversations regarding our highly innovative and groundbreaking product portfolio which is shaping the future of #cancer diagnosis and treatment. Make sure to stop by our booth to explore the latest innovations in oncology RT-PCR and #NGS clinical panels and point-of-care #solutions.

#genes2me #CancerResearch #rtpcr #Oncology #SanDiegoConference #pcr #ivd #California #diagnosis #innovative #products

#aacr 2024 #conference #g2m #genes2me #rt pcr #oncology #diagnosis #california #ivd #pcr #cancer research #san diego conference #cancer #ngs #next generation sequencing #health care #testing #kits

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precisionglobalconferences · 4 months

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Cancer and Interventional Radiology World Conference 2024

Cancer and Interventional Radiology World Conference welcomes all the students, scholars, researchers, and delegates across the globe to patronize their presence at the CIRWC 2024, September 7-9, 2024, in the USA. The CIRWC 2024 conference's primary objective is to foster a holistic medical and scientific approach to support contemporary medicines, therapies, and advancements in the discipline that aim to obliterate disease and advance wellness and healthy living. We will be delighted if you can share your eminent research advancements, recent developments, latest achievements, and insights into cancer.

We offer a forum for researchers, academicians, and medical practitioners to engage and develop interactions with fellow researchers. And discuss recent outstanding research in the field to better understand the disease. And have an idea of complications connected with recent cancer cases and combat the disease more effectively with a better approach. Cancer is the second most common cause of mortality after heart-related ailments. Cancer risk has diminished to a certain level but is still one of the foremost causes of demise rates. The recent stats state that one out of two men and three out of 2 women will be diagnosed with cancer in the coming years.

Let's join hands and visions to make it a mission to support the cancer communities and curtail the risk, advocate the latest advancements in therapy, and affirm prioritizing world health in the first place. READ MORE

#cancer conferences 2024 #oncology conference #radiology conference 2024

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jcmarchi · 9 days

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Transformative Potential of a Healthcare-Specific Foundational Model

New Post has been published on https://thedigitalinsider.com/transformative-potential-of-a-healthcare-specific-foundational-model/

Transformative Potential of a Healthcare-Specific Foundational Model

In the past two years, generalist foundational models like GPT-4 have significantly evolved, offering unprecedented capabilities due to larger datasets, increased model sizes, and architectural improvements. These models are adaptable to a wide range of tasks across various fields. However, healthcare AI is still characterized by models designed for specific tasks. For instance, a model trained to analyze X-rays for bone fractures would only identify fractures and lack the capability to generate comprehensive radiology reports. Most of the 500 AI models approved by the Food and Drug Administration are limited to one or two use cases. However, foundation models, known for their broad applicability across different tasks, are setting the stage for a transformative approach in healthcare applications.

While there have been initial attempts to develop foundational models for medical applications, this broader approach has not yet become prevalent in healthcare AI. This slow adoption is mainly due to the challenges associated with accessing large and diverse healthcare datasets, as well as the need for models to reason across different types of medical data. The practice of healthcare is inherently multimodal and incorporates information from images, electronic health records (EHRs), sensors, wearables, genomics, and more. Thus, a foundational healthcare model must also be inherently multimodal. Nonetheless, recent progress in multimodal architectures and self-supervised learning, which can handle various data types without needing labeled data, is paving the way for a healthcare foundational model.

Current State of Generative AI in Healthcare

Healthcare has traditionally been slow to adopt technology, however, it seems to have embraced Generative AI more swiftly. At HIMSS24, the largest global conference for healthcare technology professionals, Generative AI was the focal point of nearly every presentation.

One of the first use cases of Generative AI in healthcare that has seen widespread adoption focuses on alleviating the administrative load of clinical documentation. Traditionally, documenting patient interactions and care processes consumes a substantial portion of physicians’ time (>2 hrs. per day), often detracting them from direct patient care.

AI models like GPT-4 or MedPalm-2 are being used to monitor patient data and physician-patient interactions to draft key documents such as progress notes, discharge summaries, and referral letters. These drafts capture essential information accurately, requiring only physician review and approval. This significantly reduces paperwork time, allowing physicians to focus more on patient care, enhancing quality of service and reducing burnout.

However, the broader applications of foundational models in healthcare have yet to fully materialize. Generalist foundational models like GPT-4 have several limitations; thus, there is a need for a healthcare-specific foundational model. For example, GPT-4 lacks the capability to analyze medical images or understand longitudinal patient data, which is critical for providing accurate diagnoses. Additionally, it does not possess the most up-to-date medical knowledge, as it was trained on data available only up to December 2023. Google’s MedPalm-2 represents the first attempt to build a healthcare-specific foundational model, capable of both answering medical queries and reasoning about medical images. However, it still doesn’t capture full potential of AI in healthcare.

Building a Healthcare Foundational Model

The process of building a healthcare foundational model begins with data derived from both public and private sources, including biobanks, experimental data, and patient records. This model would be capable of processing and combining different data types, such as text with images or laboratory results, to perform complex medical tasks.

Additionally, it could reason about new situations and articulate its outputs in medically precise language. This capability extends to inferring and utilizing causal relationships between medical concepts and clinical data, especially when providing treatment recommendations based on observational data. For instance, it could predict acute respiratory distress syndrome from recent severe thoracic trauma and declining arterial oxygen levels, despite an increased oxygen supply.

Furthermore, the model would access contextual information from resources like knowledge graphs or databases to obtain up-to-date medical knowledge, enhancing its reasoning and ensuring that its advice reflects the latest advancements in medicine

Applications and Impact of Healthcare Foundational Model

The potential uses for a healthcare foundational model are extensive. In diagnostics, such a model could reduce the dependence on human analysis. For treatment planning, the model could aid in crafting individualized treatment strategies by considering a patient’s entire medical record, genetic details, and lifestyle factors. Some other applications include:

Grounded radiology reports: The healthcare foundational model can transform digital radiology by creating versatile assistants that support radiologists by automating report drafting and reducing workload. It would also be able to integrate entire patient history. For instance, radiologists can query the model about changes in conditions over time: “Can you identify any changes in the tumor size since the last scan?”

Bedside Clinical Decision Support: Leveraging clinical knowledge, it would offer clear, free-text explanations and data summaries, alerting medical staff to immediate patient risks and suggesting next steps. For example, the model cloud alert, “Warning: This patient is about to go into shock,” and provide links to relevant data summaries and checklists for action.

Drug Discovery: Designing proteins that bind specifically and strongly to a target is the foundation of drug discovery. Early models like RFdiffusion have begun to generate proteins based on basic inputs such as a target for binding. Building on these initial models, a healthcare-specific foundational model could be trained to understand both language and protein sequences. This would allow it to offer a text-based interface for designing proteins, potentially speeding up the development of new drugs

Challenges

Although building a healthcare-specific foundational model remains the ultimate goal, and recent advancements have made it more feasible, there are still significant challenges in developing a single model capable of reasoning across diverse medical concepts:

Data mapping multiple modalities: The model must be trained on various data modalities such as EHR data, medical imaging data, and genetic data. Reasoning across these modalities is challenging because sourcing high-fidelity data that accurately maps interactions across all these modalities is difficult. Moreover, representing various biological modalities, from cellular dynamics to molecular structures and genome-wide genetic interactions, is complex. Optimal training on human data is unfeasible and unethical, so researchers rely on less predictive animal models or cell lines, which creates a challenge in translating laboratory measurements to the intricate workings of whole organisms.

Validation and Verification: Healthcare foundational models are challenging to validate due to their versatility. Traditionally, AI models are validated for specific tasks like diagnosing a type of cancer from an MRI. However, foundational models can perform new, unseen tasks, making it hard to anticipate all possible failure modes. They require detailed explanations of their testing and approved use cases and should issue warnings for off-label use. Verifying their outputs is also complex, as they handle diverse inputs and outputs, potentially requiring a multidisciplinary panel to ensure accuracy.

Social Biases: These models risk perpetuating biases, as they may train on data that underrepresents certain groups or contains biased correlations. Addressing these biases is crucial, particularly as the scale of models increases, which can intensify the problem.

Path Forward

Generative AI has already begun to reshape healthcare by alleviating the documentation burden on clinicians, but its full potential lies ahead. The future of foundational models in healthcare promises to be transformative. Imagine a healthcare system where diagnostics are not only faster but also more accurate, where treatment plans are precisely tailored to the genetic profiles of individual patients, and where new drugs could be discovered in a few months rather than years.

Creating a healthcare-specific foundational AI model presents challenges, especially when it comes to integrating the diverse and scattered medical and clinical data. However, these obstacles can be addressed through collaborative efforts among technologists, clinicians, and policymakers. By working together, we can develop commercial frameworks that incentivize various stakeholders (EHRs, imaging companies, pathology labs, providers) to unify this data and construct AI model architectures capable of processing complex, multimodal interactions within healthcare.

Moreover, it is crucial that this advancement proceeds with a clear ethical compass and robust regulatory frameworks to ensure that these technologies are used responsibly and equitably. By maintaining high standards of validation and fairness, the healthcare community can build trust and foster acceptance among both patients and practitioners.

The journey toward fully realizing the potential of healthcare foundational models is an exciting frontier. By embracing this innovative spirit, the healthcare sector can anticipate not just meeting current challenges but transform medical science. We are on the brink of a bold new era in healthcare—one brimming with possibilities and driven by the promise of AI to improve lives on a global scale.

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