AI Research
How Artificial Intelligence Can Enhance Healthcare Research
Welcome to Health-e Law, Sheppard Mullin”s podcast exploring the fascinating health tech topics and trends of the day. In this episode, Sara Shanti welcomes Bill Kish and Dr. Brad Pruitt of Kenosha AI to explore how artificial intelligence can enhance efficiency and compliance in healthcare research.
What We Discussed in This Episode:
- What is Kenosha AI, and what is its potential role in transforming healthcare and research operations?
- Who are the end users of Kenosha AI’s products, and how are these products positioned to deliver immediate, tangible impacts for their missions?
- Looking ahead, how might this momentum build, and what direction could clinical research take with the advancements enabled by AI?
- What are the risks and concerns associated with hallucinations, synthetic data, and the trustworthiness of AI deliverables?
- Where can healthcare stakeholders feel comfortable jumping in on AI, and where does it make sense to wait for further development?
- What tasks should clinicians and researchers prioritize when exploring the potential applications of AI?
About Bill Kish
Bill Kish is the CEO and Co-Founder of Kenosha AI, bringing over 30 years of dynamic experience as a technologist, entrepreneur, and leader across five successful startups. His expertise has led burgeoning companies to flourish into multi-billion-dollar enterprises, solidifying his position as an industry innovator.
A graduate with honors in Computer Engineering from Carnegie Mellon University, Bill’s career has been defined by groundbreaking advancements in AI and machine learning applications. He co-founded Ruckus Wireless, serving as CTO and Board Director, where his contributions shaped the company into a $400M/year business and a leader in the wireless technology industry, culminating in a $1.5 billion acquisition by Brocade.
At Cogniac Corporation, Bill enabled industries to leverage AI-powered visual inspection, serving as the CEO and CTO to drive operational innovation. He also founded Jiggy AI, a boutique AI consulting firm specializing in large language model applications. Additionally, as the organizer of the Silicon Valley Machine Learning Meetup, Bill has fostered a thriving global community of over 10,000 members passionate about machine learning.
About Dr. Brad Pruitt
Dr. Brad Pruitt is the President and Co-Founder of Kenosha AI. With over 25 years of experience in clinical research and healthcare, including 13 years in the Contract Research Organization (CRO) industry, he specializes in revolutionizing clinical trials through advanced AI-powered tools like copilots and GPTs.
Dr. Pruitt is a seasoned executive and entrepreneur with a proven track record of leading ventures to success. He has held executive roles at top-tier CROs, served as the Founding CEO of an acquired startup, and contributed to three successful acquisitions in the past eight years. His prior leadership roles include Chief Medical Officer at Alethium Health Systems, where he developed go-to-market strategies for clinical trial innovation, and Senior Vice President of Medical Affairs at Safe Health, where he drove business expansion into connected diagnostics. In addition to his role with Kenosha AI, Dr. Pruitt is a Principal at Prucor and serves as a mentor and advisor for healthcare and clinical trial technology companies participating in the EvoNexus incubator program.
Dr. Pruitt earned his MD from Michigan State University College of Human Medicine and his MBA from UC San Diego’s Rady School of Management. His academic foundation, combined with his professional achievements, positions him as a visionary leader at the intersection of technology, healthcare, and clinical research.
Contact Information
Additional Resources
Kenosha AI – Kenosha AI is currently offering a free trial of its RegChatTM, which is an AI-powered Clinical Regulatory Guidance Assistant that provides a simple chat interface for answering questions about global regulatory guidance using AI and official regulatory guidance documents with referenced summarizations and multi-agency comparisons.
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MAIA platform for routine clinical testing: an artificial intelligence embryo selection tool developed to assist embryologists
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UCLA Researchers Enable Paralyzed Patients to Control Robots with Thoughts Using AI – CHOSUNBIZ – Chosun Biz
Cybersecurity firm Trail of Bits has revealed a technique that embeds malicious prompts into images processed by large language models (LLMs). The method exploits how AI platforms compress and downscale images for efficiency. While the original files appear harmless, the resizing process introduces visual artifacts that expose concealed instructions, which the model interprets as legitimate user input.
In tests, the researchers demonstrated that such manipulated images could direct AI systems to perform unauthorized actions. One example showed Google Calendar data being siphoned to an external email address without the user’s knowledge. Platforms affected in the trials included Google’s Gemini CLI, Vertex AI Studio, Google Assistant on Android, and Gemini’s web interface.
Read More: Meta curbs AI flirty chats, self-harm talk with teens
The approach builds on earlier academic work from TU Braunschweig in Germany, which identified image scaling as a potential attack surface in machine learning. Trail of Bits expanded on this research, creating “Anamorpher,” an open-source tool that generates malicious images using interpolation techniques such as nearest neighbor, bilinear, and bicubic resampling.
From the user’s perspective, nothing unusual occurs when such an image is uploaded. Yet behind the scenes, the AI system executes hidden commands alongside normal prompts, raising serious concerns about data security and identity theft. Because multimodal models often integrate with calendars, messaging, and workflow tools, the risks extend into sensitive personal and professional domains.
Also Read: Nvidia CEO Jensen Huang says AI boom far from over
Traditional defenses such as firewalls cannot easily detect this type of manipulation. The researchers recommend a combination of layered security, previewing downscaled images, restricting input dimensions, and requiring explicit confirmation for sensitive operations.
“The strongest defense is to implement secure design patterns and systematic safeguards that limit prompt injection, including multimodal attacks,” the Trail of Bits team concluded.
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