Sample Files: AI-Complaint-Assistant with prompt: Difference between revisions
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You can share your own app files on this page | You can share your own app files on this page. Please include a brief description of your app files. | ||
[[Media: | <blockquote> | ||
Description: Settings | '''''Reference files''''' | ||
[[File: ComplaintAssessmentPrompt-Schema.zip]] | |||
[[File: openFDA device_search_fields.xlsx]] | |||
<code> | |||
Settings.txt: | |||
CONFIG:OpenFDA-Vertex-V1.0 //identifies schema version | |||
Open FDA API Query specification: | |||
https_url1:api.fda.gov/device/event.json? | |||
limit1:100 | |||
REPORT | |||
report_title:Complaint Reportability Assessment | |||
// Data fields analyzed in MDR query results | |||
data1_fields:product_problems, device.brand_name, patient.patient_problems, device.manufacturer_d_name, report_number, mdr_text.text | |||
// General keyword search terms (in any field) | |||
KEYWORD1-SEARCH: | |||
// Query search fields and terms | |||
SEARCH1-FIELDS:SEARCH1-TERMS | |||
date_received:[20200101+TO+20240315] | |||
device.device_report_product_code:(FMF) | |||
// Query results sorting | |||
SORT1-FIELD:SORT1-TERM | |||
date_received:desc | |||
// Query count field/term | |||
COUNT1-FIELD:COUNT1-TERM | |||
AI CONFIGURATION & PROMPTS: | |||
// Prompt that summarizes the product problem | |||
AI-ProblemSummaryPrompt:Describe the following product problem in a couple of sentences. Include essential details. | |||
// Prompt that counts the instances of items | |||
AI-CountSummaryPrompt:List each unique item along with the count for each item. | |||
// Prompt that summarizes the problem similarity to a product problem | |||
AI-ProblemSimilarityPrompt:Analyze the similarity of this problem ({{problem_input}}) to the following problem. Use semantic similarity measurement. Present the result with the similarity score as a percentage followed by a concise explanation of the similarity score. | |||
// Prompt that analyzes the similarity between input problem and MAUDE results matching query criteria | |||
AI-MDRSimilarityPrompt:Match the most similar problem reports to this ({{problem_input}}). Include all important details. Include all reference numbers. Include the similarity scores as a percentage. Explain the similarities. Use semantic similarity measurements. Present results in descending similarity scores. For each matching result, include the matching report number followed by the similarity score followed by a brief description of the problem followed by an explanation of the similarities. | |||
// Prompt that summarizes the most similar problems | |||
AI-ReportSummaryPrompt: List the top matching problem reports with the highest similarity scores. Include all details about the matching problems. | |||
// Maximum number of words in each intermediate report. | |||
AI-WordsPerReport:1500 | |||
// LLM Pro-Vision temperature index (0..1f) | |||
AI-ModelTemperature:0.05 | |||
// LLM Pro-Vision TOP_P index (0..1f) | |||
AI-ModelTopP:0.4 | |||
// LLM Pro-Vision TOP_K (Number of words for next word prediction) | |||
AI-ModelTopK:10 | |||
// LLM Maximum output words (1..2048) | |||
AI-ModelMaxOutputTokens:2048 | |||
</code> | |||
</blockquote> | |||
==Sample App Files== | |||
[[Media: Basic-Complaint-Assessment-with-prompt.zip]] | |||
Description: Settings includes filter on product code FMF and date range from 2020 to present. Prompts for matching top similar product problem codes and individual MAUDE reports using semantic similarity. | |||
Revision as of 20:28, 7 April 2024
You can share your own app files on this page. Please include a brief description of your app files.
Reference files File:ComplaintAssessmentPrompt-Schema.zip File:OpenFDA device search fields.xlsx
Settings.txt: CONFIG:OpenFDA-Vertex-V1.0 //identifies schema version
Open FDA API Query specification: https_url1:api.fda.gov/device/event.json? limit1:100
REPORT report_title:Complaint Reportability Assessment
// Data fields analyzed in MDR query results data1_fields:product_problems, device.brand_name, patient.patient_problems, device.manufacturer_d_name, report_number, mdr_text.text
// General keyword search terms (in any field) KEYWORD1-SEARCH:
// Query search fields and terms SEARCH1-FIELDS:SEARCH1-TERMS date_received:[20200101+TO+20240315] device.device_report_product_code:(FMF)
// Query results sorting SORT1-FIELD:SORT1-TERM date_received:desc
// Query count field/term COUNT1-FIELD:COUNT1-TERM
AI CONFIGURATION & PROMPTS: // Prompt that summarizes the product problem AI-ProblemSummaryPrompt:Describe the following product problem in a couple of sentences. Include essential details. // Prompt that counts the instances of items AI-CountSummaryPrompt:List each unique item along with the count for each item. // Prompt that summarizes the problem similarity to a product problem AI-ProblemSimilarityPrompt:Analyze the similarity of this problem (Template:Problem input) to the following problem. Use semantic similarity measurement. Present the result with the similarity score as a percentage followed by a concise explanation of the similarity score. // Prompt that analyzes the similarity between input problem and MAUDE results matching query criteria AI-MDRSimilarityPrompt:Match the most similar problem reports to this (Template:Problem input). Include all important details. Include all reference numbers. Include the similarity scores as a percentage. Explain the similarities. Use semantic similarity measurements. Present results in descending similarity scores. For each matching result, include the matching report number followed by the similarity score followed by a brief description of the problem followed by an explanation of the similarities. // Prompt that summarizes the most similar problems AI-ReportSummaryPrompt: List the top matching problem reports with the highest similarity scores. Include all details about the matching problems. // Maximum number of words in each intermediate report. AI-WordsPerReport:1500 // LLM Pro-Vision temperature index (0..1f) AI-ModelTemperature:0.05 // LLM Pro-Vision TOP_P index (0..1f) AI-ModelTopP:0.4 // LLM Pro-Vision TOP_K (Number of words for next word prediction) AI-ModelTopK:10 // LLM Maximum output words (1..2048) AI-ModelMaxOutputTokens:2048
Sample App Files
Media: Basic-Complaint-Assessment-with-prompt.zip Description: Settings includes filter on product code FMF and date range from 2020 to present. Prompts for matching top similar product problem codes and individual MAUDE reports using semantic similarity.