Intracerebral Haemorrhage Prediction in Patients with Complex Chronic…

[odeak]

… Diseases

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Eval details 📑

Eval name

intracerebral-haemorrhage

Eval description

This Eval is meant to predict if a patient that is suffering from a set of complex chronic diseases is likely to have an intracerebral haemorrhage (ICH), which is a type of stroke caused by a bleeding in the brain. It uses data from the following study obtained from https://zenodo.org/record/4010889 (https://doi.org/10.5061/dryad.t76hdr7zj), a multicentre, retrospective and community-based cohort study of 3594 CCPs followed up from 01/01/2013 to 31/12/2017 in primary care without a history of previous ICH episode. The cases were identified from clinical records encoded with ICD-10 (10th version of the International Classification of Diseases) in the e-SAP database of the Catalan Health Institute. This data is licensed under a CC0 1.0 license.

What makes this a useful eval?

It shows if GPT has been trained with enough studies on patients with complex chronic diseases with and without ICH to see if is able to predict this risk in relation to existing underlying chronic diseases. The study data identifies the following risk factors for ICH: HAS-BLED ≥3 [OR 3.54; 95%CI 1.88-6.68], hypercholesterolemia [OR 1.62; 95%CI 1.11-2.35], and cardiovascular disease [OR 1.48 IC95% 1.05-2.09]. The HAS_BLED ≥3 score showed a high sensitivity [0.93 CI95% 0.97-0.89] and negative predictive value [0.98 (CI95% 0.83-1.12)].

Criteria for a good eval ✅

Below are some of the criteria we look for in a good eval. In general, we are seeking cases where the model does not do a good job despite being capable of generating a good response (note that there are some things large language models cannot do, so those would not make good evals).

Your eval should be:

• Thematically consistent: The eval should be thematically consistent. We'd like to see a number of prompts all demonstrating some particular failure mode. For example, we can create an eval on cases where the model fails to reason about the physical world.
• Contains failures where a human can do the task, but either GPT-4 or GPT-3.5-Turbo could not.
• Includes good signal around what is the right behavior. This means either a correct answer for Basic evals or the Fact Model-graded eval, or an exhaustive rubric for evaluating answers for the Criteria Model-graded eval.
• Include at least 15 high quality examples.

If there is anything else that makes your eval worth including, please document it below.

Unique eval value

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Eval structure 🏗️

Your eval should

• Check that your data is in evals/registry/data/{name}
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Final checklist 👀

Submission agreement

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• I agree that my submission will be made available under an MIT license and complies with OpenAI's usage policies.

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• I understand that opening a PR, even if it meets the requirements above, does not guarantee the PR will be merged nor GPT-4 access granted.

Submit eval

• I have filled out all required fields in the evals PR form
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Failure to fill out all required fields will result in the PR being closed.

Eval JSON data

Since we are using Git LFS, we are asking eval submitters to add in as many Eval Samples (at least 5) from their contribution here:

View evals in JSON

Eval

{"input": [{"role": "system", "content": "You are an AI tasked with predicting whether patients with chronic diseases are likely to have an Intracerebral Haemorrhage (ICH). You will be given a description of the patient with relevant medical signals. Respond with only a 1 to signify if the patient is likely to have an ICH, or a 0 if the patient is not likely to have an ICH. Do not respond with any text or disclaimers, only respond with either 1 or 0."}, {"role": "user", "content": "Age: 81, Sex: 0, Dementia/Cognitive impairment: 0, Diabetes: 0, Atrial fibrillation: 0, Hipercholesterolemia: 0, ischemic cardiomyopathy: 0, Peripheral vascular disease: 0, HTA: 0, Heart Failure: 0, Thromboembolism: 0, Stroke/AIT: 0, Chronic Renal Ins: 0, Chronic liver disease: 0, Neoplasia: 0, oral anticoagulant treatment: 0, non-steroidal anti-inflammatory drugs: 1, Antiaggregants: 0, Statines: 0, Selective serotonin reuptake inhibitors: 0, HAS-BLED score: 2"}], "ideal": "0"}
{"input": [{"role": "system", "content": "You are an AI tasked with predicting whether patients with chronic diseases are likely to have an Intracerebral Haemorrhage (ICH). You will be given a description of the patient with relevant medical signals. Respond with only a 1 to signify if the patient is likely to have an ICH, or a 0 if the patient is not likely to have an ICH. Do not respond with any text or disclaimers, only respond with either 1 or 0."}, {"role": "user", "content": "Age: 61, Sex: 0, Dementia/Cognitive impairment: 0, Diabetes: 0, Atrial fibrillation: 0, Hipercholesterolemia: 1, ischemic cardiomyopathy: 1, Peripheral vascular disease: 0, HTA: 1, Heart Failure: 0, Thromboembolism: 0, Stroke/AIT: 0, Chronic Renal Ins: 0, Chronic liver disease: 0, Neoplasia: 0, oral anticoagulant treatment: 0, non-steroidal anti-inflammatory drugs: 1, Antiaggregants: 1, Statines: 1, Selective serotonin reuptake inhibitors: 1, HAS-BLED score: 3"}], "ideal": "0"}
{"input": [{"role": "system", "content": "You are an AI tasked with predicting whether patients with chronic diseases are likely to have an Intracerebral Haemorrhage (ICH). You will be given a description of the patient with relevant medical signals. Respond with only a 1 to signify if the patient is likely to have an ICH, or a 0 if the patient is not likely to have an ICH. Do not respond with any text or disclaimers, only respond with either 1 or 0."}, {"role": "user", "content": "Age: 81, Sex: 1, Dementia/Cognitive impairment: 0, Diabetes: 1, Atrial fibrillation: 0, Hipercholesterolemia: 0, ischemic cardiomyopathy: 0, Peripheral vascular disease: 1, HTA: 1, Heart Failure: 1, Thromboembolism: 1, Stroke/AIT: 0, Chronic Renal Ins: 0, Chronic liver disease: 1, Neoplasia: 0, oral anticoagulant treatment: 0, non-steroidal anti-inflammatory drugs: 0, Antiaggregants: 1, Statines: 0, Selective serotonin reuptake inhibitors: 1, HAS-BLED score: 4"}], "ideal": "1"}
{"input": [{"role": "system", "content": "You are an AI tasked with predicting whether patients with chronic diseases are likely to have an Intracerebral Haemorrhage (ICH). You will be given a description of the patient with relevant medical signals. Respond with only a 1 to signify if the patient is likely to have an ICH, or a 0 if the patient is not likely to have an ICH. Do not respond with any text or disclaimers, only respond with either 1 or 0."}, {"role": "user", "content": "Age: 93, Sex: 1, Dementia/Cognitive impairment: 1, Diabetes: 0, Atrial fibrillation: 1, Hipercholesterolemia: 1, ischemic cardiomyopathy: 0, Peripheral vascular disease: 0, HTA: 1, Heart Failure: 1, Thromboembolism: 0, Stroke/AIT: 0, Chronic Renal Ins: 1, Chronic liver disease: 0, Neoplasia: 1, oral anticoagulant treatment: 1, non-steroidal anti-inflammatory drugs: 1, Antiaggregants: 1, Statines: 1, Selective serotonin reuptake inhibitors: 1, HAS-BLED score: 5"}], "ideal": "1"}
{"input": [{"role": "system", "content": "You are an AI tasked with predicting whether patients with chronic diseases are likely to have an Intracerebral Haemorrhage (ICH). You will be given a description of the patient with relevant medical signals. Respond with only a 1 to signify if the patient is likely to have an ICH, or a 0 if the patient is not likely to have an ICH. Do not respond with any text or disclaimers, only respond with either 1 or 0."}, {"role": "user", "content": "Age: 79, Sex: 1, Dementia/Cognitive impairment: 0, Diabetes: 0, Atrial fibrillation: 0, Hipercholesterolemia: 1, ischemic cardiomyopathy: 1, Peripheral vascular disease: 0, HTA: 1, Heart Failure: 1, Thromboembolism: 0, Stroke/AIT: 0, Chronic Renal Ins: 0, Chronic liver disease: 0, Neoplasia: 0, oral anticoagulant treatment: 1, non-steroidal anti-inflammatory drugs: 0, Antiaggregants: 1, Statines: 1, Selective serotonin reuptake inhibitors: 0, HAS-BLED score: 5"}], "ideal": "1"}