理論から実践へ 薬局におけるAIの評価
Steven M Smoke1, Alice Hou2, Scott D Nelson2
1RWJBarnabas Health, West Orange, NJ, USA.
まとめ
薬剤師は人工知能 (AI) モデルの評価を理解し,患者のケアと薬局の運営を改善する必要があります. このガイドは,薬剤師がAIの研究とメトリックを批判的に評価して 効果的な統合を図るのに役立ちます.
科学分野:
- 薬局の実践
- 医療情報学
- 医療における人工知能
背景:
- 人工知能 (AI) は医療,特に薬局においてますます重要になってきています.
- 薬剤師はAIモデルと研究を 効果的に実施するためのスキルが必要です
- AIの評価を理解することは 薬局におけるその可能性を活用する鍵です
研究 の 目的:
- AIモデルと研究を評価するためのガイドを薬剤師に提供する.
- AIの定義,データ,集団,訓練プロセスの批判的評価を強調する.
- 医療におけるAIの共通性能指標について議論する.
主な方法:
- 薬局の実践に関連するAIモデル評価の原則のレビュー
- データの品質と検証を含むAI研究の評価における重要な構成要素の議論
- AI研究で使用される標準的なパフォーマンスメトリックの説明.
主要な成果:
- 薬剤師はAIモデルを 基本的な原理を理解することで 効果的に評価することができます
- 人工知能の研究の批判的評価は 責任ある効果的な技術統合を保証します
- 人工知能の評価メトリクスの知識は,情報に基づいた意思決定に役立ちます.
結論:
- AIは薬局の実践と患者ケアを 変革する大きな可能性を秘めています
- 薬剤師にAIの評価能力を与えることは 責任ある実施に不可欠です
- 人工知能を統合する全体的なアプローチは 患者のケアと運用効率を高めます
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