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May et al discuss one of the most common laboratory tests we order, the complete blood cell count, and how to interpret and unlock additional information that we often overlook.
Singh et al explain the utility and limitations of assessing hepatic fibrosis in patients with known liver disease using specialized and increasingly available imaging techniques in patients with common diseases that may progress to liver failure.
Using several clinical scenarios, Suresh explores the limitations of serologic testing in patients with a potential “autoimmune” or systemic inflammatory syndrome (which, based on new consultations I see in my rheumatology clinic, seems to be virtually everyone who has experienced pain or fatigue).
The Journal also continues our ongoing series on Smart Testing that has focused on tests and testing strategies that have a strong evidence basis to support or discourage their utilization in specific settings. But in most real-life clinical scenarios, relatively little directly applicable evidence can be brought to bear on our decision process with a specific patient. Hence the ongoing need for each of us to refine our clinical reasoning skills, and to recognize the continuing challenges facing the incorporation of artificial intelligence and algorithmic practice into the management of the individual patient sitting or lying in front of us.
The challenge is to balance input from Watson, “Dr. Google,” our accumulated anecdotal and group experience, and specific data from the patient’s physical examination and provided history. All these sources are valuable, and I believe that how we thoughtfully and purposefully weigh and incorporate this information into practice defines us as the clinicians we are.
May et al discuss one of the most common laboratory tests we order, the complete blood cell count, and how to interpret and unlock additional information that we often overlook.
Singh et al explain the utility and limitations of assessing hepatic fibrosis in patients with known liver disease using specialized and increasingly available imaging techniques in patients with common diseases that may progress to liver failure.
Using several clinical scenarios, Suresh explores the limitations of serologic testing in patients with a potential “autoimmune” or systemic inflammatory syndrome (which, based on new consultations I see in my rheumatology clinic, seems to be virtually everyone who has experienced pain or fatigue).
The Journal also continues our ongoing series on Smart Testing that has focused on tests and testing strategies that have a strong evidence basis to support or discourage their utilization in specific settings. But in most real-life clinical scenarios, relatively little directly applicable evidence can be brought to bear on our decision process with a specific patient. Hence the ongoing need for each of us to refine our clinical reasoning skills, and to recognize the continuing challenges facing the incorporation of artificial intelligence and algorithmic practice into the management of the individual patient sitting or lying in front of us.
The challenge is to balance input from Watson, “Dr. Google,” our accumulated anecdotal and group experience, and specific data from the patient’s physical examination and provided history. All these sources are valuable, and I believe that how we thoughtfully and purposefully weigh and incorporate this information into practice defines us as the clinicians we are.
May et al discuss one of the most common laboratory tests we order, the complete blood cell count, and how to interpret and unlock additional information that we often overlook.
Singh et al explain the utility and limitations of assessing hepatic fibrosis in patients with known liver disease using specialized and increasingly available imaging techniques in patients with common diseases that may progress to liver failure.
Using several clinical scenarios, Suresh explores the limitations of serologic testing in patients with a potential “autoimmune” or systemic inflammatory syndrome (which, based on new consultations I see in my rheumatology clinic, seems to be virtually everyone who has experienced pain or fatigue).
The Journal also continues our ongoing series on Smart Testing that has focused on tests and testing strategies that have a strong evidence basis to support or discourage their utilization in specific settings. But in most real-life clinical scenarios, relatively little directly applicable evidence can be brought to bear on our decision process with a specific patient. Hence the ongoing need for each of us to refine our clinical reasoning skills, and to recognize the continuing challenges facing the incorporation of artificial intelligence and algorithmic practice into the management of the individual patient sitting or lying in front of us.
The challenge is to balance input from Watson, “Dr. Google,” our accumulated anecdotal and group experience, and specific data from the patient’s physical examination and provided history. All these sources are valuable, and I believe that how we thoughtfully and purposefully weigh and incorporate this information into practice defines us as the clinicians we are.
