I have little doubt that an AI chatbot can provide misleading information - leading to frustration for the patient and their healthcare providers. Its validity depends on how the patient frames the question and what background we provide it. As an advocate with high standing in clinical research (FDA, NCI, CIRB … experience), I’ve found that its plain language summaries of clinical trials results to be very well done – for any that I’ve asked it to review: an application that clinical researchers should make use of! As always, it’s an advisor, and the user must vet it for accuracy – look at the provided citations, consider it as a basis to aid a conversation with a trained doctor. I use Gemini Notebook to organize my clinical picture. I find it extremely useful for helping me to organize my clinical background, current meds, supplements, and to understand my labs and other test results, … for the purpose of asking informed questions of my doctors. I wrote the following for a newsletter I publish in my community: Chatbot Responses have Two Levels of Reliability Obviously, knowing whether an AI Chatbot is using a fact-checked source is critical. See _Weighing AI’s Response_ (below). **Standard AI chatbots** can confidently make up false information (called hallucinations). **RAG-regulated AI chatbots** provide **evidence-based information**. With this enabled (turned on by the nature of your question it seems) the Chatbot must look up the facts in a verified database _before_ it answers you. ### So, which is it? Is it Evidence-based or a Hallucination? **Look for the links:** Real evidence-based RAG AI will provide specific, clickable source links or footnotes next to its facts. These are called references or citations. Look for live prompts like _“Searching [Database Name]”_ or _“Reviewing source documents”_ before the AI answers. **Be skeptical of “naked” text** : If an AI gives you a highly specific medical dose or a complex climate statistic without a single link or citation, assume it is a hallucination until proven otherwise. In fact, no matter the source, providing information without a citation is a red flag warning! **Make sure you have provided accurate background information** : Is your diagnosis correct? Have you provided your age, other medical conditions, and a complete list of your medicines and supplements, for example? And how we ask the question can contribute to the reliability of the response, such as by asking for the current standard of care, or best practice, or when considering a treatment decision: _What are the risks and benefits for TREATMENT X to treat CONDITION Y, and what is the level of evidence for each?_ Probably the best course of action for concerned physicians (and thank you for that!) is to use AI for your own medical circumstance so you can provide informed guidance to patients about its strengths and dangers.

I have little doubt that an AI chatbot can provide misleading information - leading to frustration for the patient and their healthcare providers. Its validity depends on how the patient frames the question and what background we provide it. As a advocate with high standing in clinical research (FDA, NCI, CIRB … experience), I’ve found that its plain language summaries of clinical trials results to be very well done – for any that I’ve asked it to review: an application that clinical researchers should make use of! As always, it’s an advisor, and the user must vet it for accuracy – look at the provided citations, consider it as a basis to aid a conversation with a trained doctor. I use Gemini Notebook to organize my clinical picture. I find it extremely useful for helping me to organize my clinical background, current meds, supplements, and to understand my labs and other test results, … for the purpose of asking informed questions of my doctors. I wrote the following for a newsletter I publish in my community: Chatbot Responses have Two Levels of Reliability Obviously, knowing whether an AI Chatbot is using a fact-checked source is critical. See _Weighing AI’s Response_ (below). **Standard AI chatbots** can confidently make up false information (called hallucinations). **RAG-regulated AI chatbots** provide **evidence-based information**. With this enabled (turned on by the nature of your question it seems) the Chatbot must look up the facts in a verified database _before_ it answers you. ### So, which is it? Is it Evidence-based or a Hallucination? **Look for the links:** Real evidence-based RAG AI will provide specific, clickable source links or footnotes next to its facts. These are called references or citations. Look for live prompts like _“Searching [Database Name]”_ or _“Reviewing source documents”_ before the AI answers. **Be skeptical of “naked” text** : If an AI gives you a highly specific medical dose or a complex climate statistic without a single link or citation, assume it is a hallucination until proven otherwise. In fact, no matter the source, providing information without a citation is a red flag warning! **Make sure you have provided accurate background information** : Is your diagnosis correct? Have you provided your age, other medical conditions, and a complete list of your medicines and supplements, for example? And how we ask the question can contribute to the reliability of the response, such as by asking for the current standard of care, or best practice, or when considering a treatment decision: _What are the risks and benefits for TREATMENT X to treat CONDITION Y, and what is the level of evidence for each?_ Probably the best course of action for concerned physicians (and thank you for that!) is to use AI for your own medical circumstance so you can provide informed guidance to patients about its strengths and dangers.

I have little doubt that an AI chatbot can provide misleading information - leading to frustration for the patient and their healthcare providers. Its validity depends on how the patient frames the question and what background we provide it. As a advocate with high standing in clinical research (FDA, NCI, CIRB … experience), I’ve found that its plain language summaries of clinical trials results to be very well done – for any that I’ve asked it to review: an application that clinical researchers should make use of! As always, it’s an advisor, and the user must vet it for accuracy – look at the provided citations, consider it as a basis to aid a conversation with a trained doctor. I use Gemini Notebook to organize my clinical picture. I find it extremely useful for helping me to organize my clinical background, current meds, supplements, and to understand my labs and other test results, … for the purpose of asking informed questions of my doctors. I wrote the following for a newsletter I publish in my community: Chatbot Responses have Two Levels of Reliability Obviously, knowing whether an AI Chatbot is using a fact-checked source is critical. See _Weighing AI’s Response_ (below). **Standard AI chatbots** can confidently make up false information (called hallucinations). **RAG-regulated AI chatbots** provide **evidence-based information**. With this enabled (turned on by the nature of your question it seems) the Chatbot must look up the facts in a verified database _before_ it answers you. ### So, which is it? Is it Evidence-based or a Hallucination? **Look for the links:** Real evidence-based RAG AI will provide specific, clickable source links or footnotes next to its facts. These are called references or citations. Look for live prompts like _“Searching [Database Name]”_ or _“Reviewing source documents”_ before the AI answers. **Be skeptical of “naked” text** : If an AI gives you a highly specific medical dose or a complex climate statistic without a single link or citation, assume it is a hallucination until proven otherwise. In fact, no matter the source, providing information without a citation is a red flag warning! **Make sure you have provided accurate background information** : Is your diagnosis correct? Have you provided your age, other medical conditions, and a complete list of your medicines and supplements, for example? And how we ask the question can contribute to the reliability of the response, such as by asking for the current standard of care, or best practice, or when considering a treatment decision: _What are the risks and benefits for TREATMENT X to treat CONDITION Y, and what is the level of evidence for each?_ Probably the best course of action for concerned physicians (and thank you for that!) is to use AI for your own medical circumstance so you can provide informed guidance to patients about its strengths and dangers.

The Liberal government's marquee fall legislation is expected to strengthen a controversial section of the Labour Code, two senior government sources tell CBC News.

The Liberal government's marquee fall legislation is expected to strengthen a controversial section of the Labour Code, two senior government sources tell CBC News.

YouTube video by Reese Waters

YouTube video by Reese Waters

YouTube video by Reese Waters

YouTube video by Reese Waters

YouTube video by Reese Waters

YouTube video by Reese Waters

YouTube video by Reese Waters

YouTube video by Reese Waters

YouTube video by Reese Waters

YouTube video by Reese Waters

YouTube video by Reese Waters

YouTube video by Blackmore's Night - Topic

After more than two weeks on the picket line, Bank of Canada security workers have secured a major victory. The Canada Industrial Relations Board (CIRB) has ruled that the Bank of Canada violated the ...

The dispute involving 42 Ottawa and seven Montreal officers prompted the Bank of Canada to close its Montreal facility and move critical and time-sensitive operations to Toronto, while the CIRB has…