There’s no shortage of resources for healthcare workers who wish they knew AI well enough to talk shop with the technology pros who develop the models. The problem is weeding through the offerings to get to what will really work for you. 

Happily, a seasoned technology and business writer has done a good deal of the legwork for all interested parties. 

“A successful learning journey in AI involves commitment, curiosity and the right resources,” explains Kathryn Pearl Timonera of eWeek. “You can develop a thorough understanding of AI concepts and applications by reading foundational books, experimenting with AI platforms and participating actively in AI communities.”

Expounding on these and other pointers, Timonera lays out five AI learning pathways that anyone can explore without overspending on anything. Here are excerpts from her listicle. 

1. Master the fundamentals of programming. 

Beginner-friendly platforms such as Codecademy and FreeCodeCamp offer courses that combine theory with hands-on practice, “allowing you to get practical programming experience and solve real-world problems by building data processing programs, analyzing datasets and experimenting with data visualization,” Timonera reports. More: 

‘You can also participate in coding challenges on websites such as LeetCode, HackerRank and CodeSignal as a way to improve your coding skills by working with large datasets and optimizing algorithms for AI.’

2. Learn data structures and algorithms. 

“There are many free resources to help you learn and understand data structures and algorithms, which allow effective data processing and problem-solving in AI models,” Timonera writes. “YouTube channels such as FreeCodeCamp and CS50 offer free, extensive tutorials on these topics.” More: 

‘In addition, online learning platform Great Learning offers free courses, and AI specialists gather in online communities like Kaggle and GitHub to share knowledge and ask and answer questions.’

3. Study machine learning and deep learning basics.

Machine learning is a subset of AI that allows computers to learn from data without being explicitly programmed, Timonera reminds, while deep learning uses neural networks to mimic how the human brain processes information. FreeCodeCamp offers costless courses in machine and deep learning for intermediate learners as well as beginners, she notes. Meanwhile: 

‘Kaggle offers real-world datasets for practicing machine learning in fields such as finance and healthcare, which you can use to develop prediction models for hands-on experience.’

4. Engage with AI communities. 

Online communities and forums provide “excellent opportunities for enthusiasts to share knowledge and collaborate on projects,” Timonera points out. “GitHub is a place for developers to collaborate on AI projects and share code repositories.” More: 

‘Facebook Groups, Slack Communities and LinkedIn provide professional networks where you can interact with experts, attend webinars and participate in collaborative projects.’

5. Keep current with AI trends and technologies.

AI is constantly changing, with new tools powered by new models and new use cases appearing regularly, Timonera writes. Keeping up to date allows you to better understand the new developments in machine learning, deep learning and AI applications, “which in turn lets you expand your abilities, capitalize on developing technologies and pursue new opportunities in fields where AI is being used.” More:  

‘The best way to stay up to date with AI’s latest trends is to join AI-related community groups and subscribe to industry leaders’ newsletters, such as those published by OpenAI, Google, IBM, AWS and Microsoft.’

“Whether you want to master deep learning, explore AI-powered tools or create creative solutions, your journey will be influenced by continuous learning and hands-on experience,” Timonera notes. “Stay open to ideas, explore collaborations and be willing to experiment, as AI’s revolutionary power provides limitless possibilities for growth and innovation.”

There’s more. Read the whole thing. 

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Buzzworthy developments of the past few days.

• Building a new hospital with emerging technologies throughout? Remember this. Some of today’s leading edges are tomorrow’s fading gadgets—and some are only just taking shape. Jeremy Meller, CIO of Children’s Healthcare of Atlanta, makes the observation one month after the opening of the Arthur M. Blank Pediatric Hospital. That’s the 2 million-square-foot facility that has a fleet of 90 robots reporting for duty each day and all sorts of other high-tech niceties. “The technology landscape changes quickly,” Meller tells Health System CIO. Some of the things hospital leadership readied for in the earliest planning phases “haven’t really quite come to fruition yet,” he says, “but there’s other things—like AI, video and video combined with AI—that have progressed faster than we had anticipated a few years ago.” 
   
• Many if not most of today’s software developers use AI coding tools every day. Yet nearly 40% have little to no trust in AI-generated code. This shouldn’t be surprising, since coders work under productivity pressures and on deadlines. Putting quantity over quality has to be a major temptation. In any case, the findings are from Google’s latest “State of DevOps” report, which also shows more than 75% of surveyed developers use AI to perform daily tasks. The low trust level “indicates to us that there is a need to manage AI integration more thoughtfully,” the report’s authors remark. “Teams must carefully evaluate AI’s role in their development workflow to mitigate the downsides.” IT Pro puts the findings in context with those from other studies. 
   
• Creations from healthcare AI players Abridge, Google DeepMind and Laguna Insight have made Time magazine’s list of the 200 best inventions of 2024. A bunch of other healthcare innovators are in there too, although not necessarily because they use AI. In fact, the editors break off medical care and home health as categories unto themselves. Browse the list. 
   
• Two years after OpenAI introduced its Whisper transcription system, healthcare people are whispering about it behind its back. The chatter took off after the Associated Press ran a story Oct. 26 under the headline “Researchers say an AI-powered transcription tool used in hospitals invents things no one ever said.” Interestingly, Whisper defenders have been stepping up on the software’s behalf. At Tom’s Hardware, for example, one reader calls the AP headline “misleading clickbait” while another points out: “As with all things voice recognition, you still need to always review what initially comes out, even with a fine-tuned model.”
   
• The role of chief AI officer may be new, but it’s already evolving too. That’s as true in healthcare as in any other sector. A knowledgeable mover and shaker behind the title’s rise discusses the dynamics in an interview with HIMSS Media’s Healthcare IT News. “I think it’s an evolving role in how it’s defined, how organizations are thinking about it,” says Dennis Chornenky, chief AI adviser at UC Davis Health and CEO of Domelabs AI. “But I think it is a very multidimensional role, and it’s very important for organizations to keep that in mind.” Read the rest.
   
• Precision medicine AI company Tempus is working with Northwestern Medicine to propel AI applications from research settings to care sites. They’re starting with cardiovascular care at Northwestern’s Bluhm Cardiovascular Institute. The initiating project will have Bluhm clinicians using Tempus technology to identify patients at risk of developing atrial fibrillation or structural heart disease. Announcement. 
   
• The second generation of Seno Medical’s AI-equipped optoacoustic breast-imaging system has passed muster. Reporting the results in Academic Radiology, researchers state they found the Gen 2 Imagio to be at least as good as its Gen 1 forerunner. In both versions, the innovative device combines ultrasound scans with laser optics and AI aids to visualize tumor morphology as well as structure—a dual approach that “can increase specificity without decreasing sensitivity in a real-world setting,” the study authors write. Announcement. 
   
• Recent research in the news: 
   
  • Wayne State University: AI computer models may make development of new drugs easier and more cost-effective
     
  • Virginia Tech: Researcher finds AI could help improve city planning 
     
  • Penn State: Personal info and privacy control may be key to better visits with AI doctors
     
  • University of Michigan: Accounting for bias in medical data helps prevent AI from amplifying racial disparity
     
  • Washington University: Complexity of tumors revealed in 3D
     
• Funding news of note:
   
  • UK-Based healthtech startup Definition Health raises £5.75M ($7.4M) in pre-seed funding to streamline surgical care with advanced predictive AI technology
     
• From AIin.Healthcare’s news partners:
   
  • Cardiovascular Business: AI-enabled plaque assessments help cardiologists ID high-risk CAD patients
     
  • Radiology Business: Real-world use of AI algorithm for collapsed lung cuts radiologist reporting times by 46%
     
  • Health Imaging: Wearable ultrasound device monitors muscle activity with great precision
     
  • Radiology Business: Elon Musk urges users to submit X-ray, PET and MR images to xAI chatbot Grok
     
  • Health Imaging: AI tumor volume estimations could improve prostate cancer treatment strategies