AI-Analysis-Assistant - Revision history

Waghanna at 23:04, 29 May 2024

2024-05-29T23:04:29Z

← Older revision		Revision as of 23:04, 29 May 2024
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	AI-ProblemSummaryPrompt: // Prompt that summarizes the product problem		AI-ProblemSummaryPrompt: // Prompt that summarizes the product problem

	~~AI-CountSummaryPrompt: // Prompt that counts the instances of items~~

	AI-AnalysisPrompt: // Prompt that analyzes the MDR data to identify trends and patterns in adverse event occurrence		AI-AnalysisPrompt: // Prompt that analyzes the MDR data to identify trends and patterns in adverse event occurrence
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	AI-ReportSummaryPrompt: // Prompt that summarizes the information collected from the MDR records		AI-ReportSummaryPrompt: // Prompt that summarizes the information collected from the MDR records

	AI-WordsPerReport: // Number of words in each intermediate report (recommended: ~~1500~~, range: 100-~~5000~~)		AI-WordsPerReport: // Number of words in each intermediate report (recommended: 10000, range: 100-30000)

	AI-ModelTemperature: // LLM Temperature index (recommended: 0.05, range: 0..1f)		AI-ModelTemperature: // LLM Temperature index (recommended: 0.05, range: 0..1f)

	AI-ModelTopP: // LLM TOP_P index (recommended: 0.4, range: 0..1f)		AI-ModelTopP: // LLM TOP_P index (recommended: 1.0, range: 0..1f)

	AI-ModelTopK: // LLM TOP_K number of words for next word prediction (recommended: 10, range: 1-128)		AI-ModelTopK: // LLM TOP_K number of words for next word prediction (recommended: 2, range: 1-128)

	AI-ModelMaxOutputTokens: // LLM maximum output words (range: 1-~~2048~~)		AI-ModelMaxOutputTokens: // LLM maximum output words (range: 1-8192)
	\|}		\|}
	</blockquote>		</blockquote>

Waghanna at 21:56, 15 April 2024

2024-04-15T21:56:20Z

← Older revision		Revision as of 21:56, 15 April 2024
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	==App Description==		==App Description==

	'''Use ~~case~~:'''		'''App Use Case:'''
	The AI-Analysis-Assistant app is a powerful tool designed to enhance decision-making and productivity by leveraging artificial intelligence and data mining of vast amounts of data, specifically focused on adverse events (MAUDE: Manufacturer and User Facility Device Experience). It supports a wide range of data analysis tasks using natural language and includes highly extensible options for analyzing unstructured data. From summarizing data analytics and trends to uncovering hidden patterns and insights, to simulating what-if scenarios with objective data-driven results, the Analysis-Assistant app enables users to consider multiple factors, analyze vast amounts of data efficiently, and make well-informed, bias-free decisions.		The AI-Analysis-Assistant app is a powerful tool designed to enhance decision-making and productivity by leveraging artificial intelligence and data mining of vast amounts of data, specifically focused on adverse events (MAUDE: Manufacturer and User Facility Device Experience). It supports a wide range of data analysis tasks using natural language and includes highly extensible options for analyzing unstructured data. From summarizing data analytics and trends to uncovering hidden patterns and insights, to simulating what-if scenarios with objective data-driven results, the Analysis-Assistant app enables users to consider multiple factors, analyze vast amounts of data efficiently, and make well-informed, bias-free decisions.

	'''~~Model description~~:'''		'''App Functionality:'''
	The AI-Analysis-Assistant app reads a Settings file that contains criteria for adverse events and pulls the up to date matching records from MAUDE. The unstructured data is then chunked to optimize semantic vector processing adopting a retrieval augmented generation approach. The model then performs the data analysis prompts given in the Settings file on the data chunked data and injects the results in a predefined report template.		The AI-Analysis-Assistant app reads a Settings file that contains criteria for adverse events and pulls the up to date matching records from MAUDE. The unstructured data is then chunked to optimize semantic vector processing adopting a retrieval augmented generation approach. The model then performs the data analysis prompts given in the Settings file on the data chunked data and injects the results in a predefined report template.

Waghanna at 19:23, 15 April 2024

2024-04-15T19:23:01Z

← Older revision		Revision as of 19:23, 15 April 2024
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	Reference file: [[Media: openFDA device_search_fields.xlsx]]		Reference file: [[Media: openFDA device_search_fields.xlsx]]

	{\| role="presentation" class="wikitable mw-collapsible mw-collapsed"		{\| role="presentation" style="min-width:250px;" class="wikitable mw-collapsible mw-collapsed code-sample"
	\| <strong>Settings.txt</strong>		\| <strong>Settings.txt</strong>
	\|-		\|-

Waghanna at 18:14, 13 April 2024

2024-04-13T18:14:55Z

← Older revision		Revision as of 18:14, 13 April 2024
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	'''[[Sample Files: AI-Analysis-Assistant]]'''		'''[[Sample Files: AI-Analysis-Assistant]]'''

	~~----~~		==App Description==

	'''Use case:'''		'''Use case:'''
	The AI-Analysis-Assistant app is a powerful tool designed to enhance decision-making and productivity by leveraging artificial intelligence and data mining of vast amounts of data, specifically focused on adverse events (MAUDE: Manufacturer and User Facility Device Experience). It supports a wide range of data analysis tasks using natural language and includes highly extensible options for analyzing unstructured data. From summarizing data analytics and trends to uncovering hidden patterns and insights, to simulating what-if scenarios with objective data-driven results, the Analysis-Assistant app enables users to consider multiple factors, analyze vast amounts of data efficiently, and make well-informed, bias-free decisions.		The AI-Analysis-Assistant app is a powerful tool designed to enhance decision-making and productivity by leveraging artificial intelligence and data mining of vast amounts of data, specifically focused on adverse events (MAUDE: Manufacturer and User Facility Device Experience). It supports a wide range of data analysis tasks using natural language and includes highly extensible options for analyzing unstructured data. From summarizing data analytics and trends to uncovering hidden patterns and insights, to simulating what-if scenarios with objective data-driven results, the Analysis-Assistant app enables users to consider multiple factors, analyze vast amounts of data efficiently, and make well-informed, bias-free decisions.

Waghanna at 18:08, 13 April 2024

2024-04-13T18:08:47Z

@@ Line 1: / Line 1: @@
 ==App Files==
 <blockquote>
@@ Line 67: / Line 55: @@
 '''[[Sample Files: AI-Analysis-Assistant]]'''

Waghanna at 21:12, 11 April 2024

2024-04-11T21:12:53Z

← Older revision		Revision as of 21:12, 11 April 2024
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	<blockquote>		<blockquote>
	Application executable: [[Media: AI-Analysis-Assistant.zip]]		Application executable: [[Media: AI-Analysis-Assistant.zip]]

	~~Reference file: [[Media: Analysis-Schema.zip]]~~

	Reference file: [[Media: openFDA device_search_fields.xlsx]]		Reference file: [[Media: openFDA device_search_fields.xlsx]]

Waghanna at 02:02, 9 April 2024

2024-04-09T02:02:34Z

← Older revision		Revision as of 02:02, 9 April 2024
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	'''Use case:'''		'''Use case:'''
	The AI-Analysis-Assistant		The AI-Analysis-Assistant app is a powerful tool designed to enhance decision-making and productivity by leveraging artificial intelligence and data mining of vast amounts of data, specifically focused on adverse events (MAUDE: Manufacturer and User Facility Device Experience). It supports a wide range of data analysis tasks using natural language and includes highly extensible options for analyzing unstructured data. From summarizing data analytics and trends to uncovering hidden patterns and insights, to simulating what-if scenarios with objective data-driven results, the Analysis-Assistant app enables users to consider multiple factors, analyze vast amounts of data efficiently, and make well-informed, bias-free decisions.

	'''Model description:'''		'''Model description:'''
	The AI-Analysis-Assistant		The AI-Analysis-Assistant app reads a Settings file that contains criteria for adverse events and pulls the up to date matching records from MAUDE. The unstructured data is then chunked to optimize semantic vector processing adopting a retrieval augmented generation approach. The model then performs the data analysis prompts given in the Settings file on the data chunked data and injects the results in a predefined report template.

	Diagram outlining the processing steps of the Analysis Assistant:		Diagram outlining the processing steps of the Analysis Assistant:
Line 9:		Line 9:
	[[Image: AI-Analysis-Process.jpg\|600px]]		[[Image: AI-Analysis-Process.jpg\|600px]]

	A PDF document is generated containing		A PDF document is generated containing the analysis results.

	==App Files==		==App Files==

Waghanna at 06:07, 8 April 2024

2024-04-08T06:07:09Z

@@ Line 1: / Line 1: @@
 '''Use case:'''
-'''Model description:'''
+limit1:   // limit of query results
-Diagram outlining the processing steps of the Analysis Assistant:
+AI-WordsPerReport:   // Number of words in each intermediate report (recommended: 1500, range: 100-5000)
-[[Image: AI-Analysis-Assistant-Process.jpg|800px]]
+AI-ModelTemperature:   // LLM Temperature index (recommended: 0.05, range: 0..1f)
-'''Reference files:'''
+AI-ModelMaxOutputTokens:   // LLM maximum output words (range: 1-2048)
-* [[Media: Sample-AI-Analysis-Assistant.zip]]
+|}
-'''Additional information:'''
+'''[[Sample Files: AI-Analysis-Assistant]]'''

Waghanna: Protected "AI-Analysis-Assistant" ([Edit=Allow only administrators] (indefinite) [Move=Allow only administrators] (indefinite))

2024-04-07T10:39:19Z

Protected "AI-Analysis-Assistant" ([Edit=Allow only administrators] (indefinite) [Move=Allow only administrators] (indefinite))

← Older revision	Revision as of 10:39, 7 April 2024
(No difference)

Waghanna at 10:25, 7 April 2024

2024-04-07T10:25:30Z

← Older revision		Revision as of 10:25, 7 April 2024
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	Diagram outlining the processing steps of the ~~Complaints~~ Assistant:		Diagram outlining the processing steps of the Analysis Assistant:

	[[Image: AI-~~Complaint~~-~~Handling~~-Process.jpg\|800px]]		[[Image: AI-Analysis-Assistant-Process.jpg\|800px]]