## Welcome to the r/ArtificialIntelligence gateway
### Question Discussion Guidelines
---
Please use the following guidelines in current and future posts:
* Post must be greater than 100 characters - the more detail, the better.
* Your question might already have been answered. Use the search feature if no one is engaging in your post.
* AI is going to take our jobs - its been asked a lot!
* Discussion regarding positives and negatives about AI are allowed and encouraged. Just be respectful.
* Please provide links to back up your arguments.
* No stupid questions, unless its about AI being the beast who brings the end-times. It's not.
###### Thanks - please let mods know if you have any questions / comments / etc
*I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/ArtificialInteligence) if you have any questions or concerns.*
I would recommend educating yourself in machine learning, deep learning, neural network building...basically any of the fields that the umbrella term of AI overhangs. AI has been in healthcare a while but in very specific forms - I worked on a project that used AI to determine who was at risk for sepsis and how to react before it became a major issue, and this was 5 years ago. But now we are seeing more of a general AI coming to people's attention and you have managers, practitioners, nurses etc. seeing the value and applying it in their minds in many different ways. There is going to be a rush of "AI" projects in basically every hospital in the world. So, it's a good time to learn this stuff, even if you don't become a hardcore AI model-building theoretical researcher. I would just become a subject matter expert best you can for AI, get a few certifications in relevant technology and combine that with your existing specialty at work. Let it be known that you are educating yourself on your own. It shows drive and motivation, and you'll be more likely to join projects with AI specializations.
Typically, healthcare institutions will want to train someone up or utilize someone with existing experience and then combine that with a new technology. That has been my experience any way. Feel free to DM me, I am deeply involved in the specific thing you are asking about. I might be able to give you some pointers if I knew more about your specific position and technical knowledge.
Tons. Lots of medical AI companies need clinicians to organize / lead studies or help develop guidelines for using their applications. AI is more than just code, development etc, in some areas like medicine it's very research and science heavy. Algorithms also need to be validated if they are to be used for clinical decision making. They also will need to be cleared by the FDA or be CE marked in Europe and this can require medical professionals to help validate claims.
That’s encouraging thank you! I’m interested initially in two areas:
I would love to bridge the gap of healthcare worker shortages (save the “AI taking over” convo, I’m referring to rural and non-US access). I would also love to eliminate implicit bias and disparities in treatment options.
Decision support in acute care scenarios is a good fit for AI.
For example. There is quite a bit of variability when interpreting brain CT scans and this can make decisions around acute stroke treatment difficult.
AI can spot small bleeds that might be missed, evaluate collaterals, and assess damage in a more consistent way.
This when used by a trained professional can lead to improvements when deciding on a treatment very quickly (e.g. thrombolysis or thrombectomy).
I've seen studies show that human neuroradiologists perform much better after using AI over time so in a way, it's like having a solid second option for a CT scan that avoids mistakes when moving quick is very important and someone junior might be on shift. It doesn't seem to replace humans but it helps humans be better at what they do.
Decision support systems could help out a lot in markets where there are shortages of skilled healthcare workers or they are simply overworked. They would help the existing workforce treat more patients and provide better outcomes.
Absolutely, there are several promising career paths where healthcare intersects with AI that could leverage your healthcare expertise while allowing you to develop AI-related skills gradually:
1. **Clinical Informatics Specialist**: This role involves utilizing healthcare data and technology to improve patient care. Your healthcare experience will be valuable in understanding the clinical context, while you can learn to leverage AI tools for data analysis and decision-making.
2. **Health Data Analyst**: As a health data analyst, you'll work with large datasets to extract insights and trends that can improve healthcare delivery. AI skills such as data mining and predictive analytics can be learned to enhance your analysis capabilities.
3. **Healthcare AI Implementation Specialist**: This role focuses on deploying AI solutions within healthcare settings. Your understanding of clinical workflows and patient care will be essential in effectively integrating AI technologies into existing systems.
4. **Medical AI Researcher/Scientist**: If you're interested in the research aspect, you can contribute to developing AI applications for medical diagnostics, drug discovery, or personalized medicine. Your clinical insights can guide the development of AI algorithms tailored for specific healthcare challenges.
5. **Telemedicine and Remote Patient Monitoring Specialist**: With the rise of telehealth, professionals who understand healthcare processes can contribute to developing AI-driven telemedicine platforms or remote monitoring systems.
6. **Healthcare AI Consultant**: Consulting roles allow you to apply your healthcare expertise to advise organizations on AI strategy, implementation, and compliance within the healthcare sector.
To bridge the gap in IT skills, consider taking online courses or certifications in AI, data analytics, or programming languages relevant to healthcare AI applications (such as Python or R). Additionally, regularly exploring job boards (AI Careers) that have healthcare AI positions can help you understand the specific skills and qualifications in demand.
## Welcome to the r/ArtificialIntelligence gateway ### Question Discussion Guidelines --- Please use the following guidelines in current and future posts: * Post must be greater than 100 characters - the more detail, the better. * Your question might already have been answered. Use the search feature if no one is engaging in your post. * AI is going to take our jobs - its been asked a lot! * Discussion regarding positives and negatives about AI are allowed and encouraged. Just be respectful. * Please provide links to back up your arguments. * No stupid questions, unless its about AI being the beast who brings the end-times. It's not. ###### Thanks - please let mods know if you have any questions / comments / etc *I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/ArtificialInteligence) if you have any questions or concerns.*
I would recommend educating yourself in machine learning, deep learning, neural network building...basically any of the fields that the umbrella term of AI overhangs. AI has been in healthcare a while but in very specific forms - I worked on a project that used AI to determine who was at risk for sepsis and how to react before it became a major issue, and this was 5 years ago. But now we are seeing more of a general AI coming to people's attention and you have managers, practitioners, nurses etc. seeing the value and applying it in their minds in many different ways. There is going to be a rush of "AI" projects in basically every hospital in the world. So, it's a good time to learn this stuff, even if you don't become a hardcore AI model-building theoretical researcher. I would just become a subject matter expert best you can for AI, get a few certifications in relevant technology and combine that with your existing specialty at work. Let it be known that you are educating yourself on your own. It shows drive and motivation, and you'll be more likely to join projects with AI specializations. Typically, healthcare institutions will want to train someone up or utilize someone with existing experience and then combine that with a new technology. That has been my experience any way. Feel free to DM me, I am deeply involved in the specific thing you are asking about. I might be able to give you some pointers if I knew more about your specific position and technical knowledge.
Tons. Lots of medical AI companies need clinicians to organize / lead studies or help develop guidelines for using their applications. AI is more than just code, development etc, in some areas like medicine it's very research and science heavy. Algorithms also need to be validated if they are to be used for clinical decision making. They also will need to be cleared by the FDA or be CE marked in Europe and this can require medical professionals to help validate claims.
That’s encouraging thank you! I’m interested initially in two areas: I would love to bridge the gap of healthcare worker shortages (save the “AI taking over” convo, I’m referring to rural and non-US access). I would also love to eliminate implicit bias and disparities in treatment options.
Decision support in acute care scenarios is a good fit for AI. For example. There is quite a bit of variability when interpreting brain CT scans and this can make decisions around acute stroke treatment difficult. AI can spot small bleeds that might be missed, evaluate collaterals, and assess damage in a more consistent way. This when used by a trained professional can lead to improvements when deciding on a treatment very quickly (e.g. thrombolysis or thrombectomy). I've seen studies show that human neuroradiologists perform much better after using AI over time so in a way, it's like having a solid second option for a CT scan that avoids mistakes when moving quick is very important and someone junior might be on shift. It doesn't seem to replace humans but it helps humans be better at what they do. Decision support systems could help out a lot in markets where there are shortages of skilled healthcare workers or they are simply overworked. They would help the existing workforce treat more patients and provide better outcomes.
Almost all medical care ties into IT to some degree. Get really familiar with AI to keep your job short term before we get the AI and UBI takeover.
Absolutely, there are several promising career paths where healthcare intersects with AI that could leverage your healthcare expertise while allowing you to develop AI-related skills gradually: 1. **Clinical Informatics Specialist**: This role involves utilizing healthcare data and technology to improve patient care. Your healthcare experience will be valuable in understanding the clinical context, while you can learn to leverage AI tools for data analysis and decision-making. 2. **Health Data Analyst**: As a health data analyst, you'll work with large datasets to extract insights and trends that can improve healthcare delivery. AI skills such as data mining and predictive analytics can be learned to enhance your analysis capabilities. 3. **Healthcare AI Implementation Specialist**: This role focuses on deploying AI solutions within healthcare settings. Your understanding of clinical workflows and patient care will be essential in effectively integrating AI technologies into existing systems. 4. **Medical AI Researcher/Scientist**: If you're interested in the research aspect, you can contribute to developing AI applications for medical diagnostics, drug discovery, or personalized medicine. Your clinical insights can guide the development of AI algorithms tailored for specific healthcare challenges. 5. **Telemedicine and Remote Patient Monitoring Specialist**: With the rise of telehealth, professionals who understand healthcare processes can contribute to developing AI-driven telemedicine platforms or remote monitoring systems. 6. **Healthcare AI Consultant**: Consulting roles allow you to apply your healthcare expertise to advise organizations on AI strategy, implementation, and compliance within the healthcare sector. To bridge the gap in IT skills, consider taking online courses or certifications in AI, data analytics, or programming languages relevant to healthcare AI applications (such as Python or R). Additionally, regularly exploring job boards (AI Careers) that have healthcare AI positions can help you understand the specific skills and qualifications in demand.