JP2022035870A - 検査結果推定装置およびプログラム - Google Patents
検査結果推定装置およびプログラム Download PDFInfo
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Abstract
Description
図1および図2は、本実施形態における検査結果推定システム100(以下、単に「システム100」という)の構成の概要を説明するための図である。システム100は、心電信号Saが入力されると、心臓超音波検査結果Raを推定して出力するためのシステムであり、医師による診断や治療を支援するためのシステムである。ここで、「心臓超音波検査結果Ra」は、心臓超音波検査(心エコー検査)を実施した場合に得られる検査結果に相当するものであり、例えば、心電信号Saのみでは得られない心臓の構造的な情報や心臓における血液の流量等の情報が含まれる。心臓超音波検査結果Raの詳細は、図10を用いて後述する。
図2に示すように、システム100は、複数の検査結果推定装置10と、機械学習装置20とを備える。機械学習装置20は、図1に示した学習フェーズを実行するための装置である。すなわち、機械学習装置20は、学習用心電信号SLを入力データとし学習用心臓超音波検査結果RLを教師データとするデータセットを用いて、機械学習を行うことにより、学習済モデルを作成する。検査結果推定装置10は、図1に示した推定フェーズを実行するための装置である。すなわち、検査結果推定装置10は、学習済モデルMを用いて、入力された心電信号Saに対応する心臓超音波検査結果Raを推定し、推定された心臓超音波検査結果Raを出力する。
心電図検査装置30は、例えば、12誘導心電図を用いた検査法により、心電図検査を行うように構成されている。図3および図4に示すように、心電図検査装置30は、測定部31と、制御部32と、通信部33と、表示部34とを含む。以下、12誘導心電図を例として示すが、本開示では、12誘導心電図を用いた検査法以外の検査法により心電信号Saを取得してもよい。
図2に示すように、機械学習装置20は、制御部21と、記憶部22と、通信部23と、入力部24とを含む。制御部21は、プログラムを実行することにより制御処理を実行するプロセッサを含む。そして、制御部21は、機械学習装置20の各制御処理を実行するように構成されている。記憶部22は、学習用データ記憶領域22aと、学習済モデル記憶領域22bとを含む。通信部23は、通信インターフェイスであり、ネットワークNに接続されている。入力部24は、キーボード、マウス、タッチパネル等のユーザインタフェースであってもよいし、紙媒体を読み取る光学式文字読取装置(OCR)として構成されていてもよい。
図8は、検査結果推定装置10の構成を示すブロック図である。検査結果推定装置10は、制御部11と、記憶部12と、通信部13と、表示部14とを含む。制御部11は、制御部11は、プログラムを実行することにより制御処理を実行するプロセッサを含む。そして、制御部11は、検査結果推定装置10の各制御処理を実行するように構成されている。
次に、図13を参照して、本実施形態における学習済モデルの作成方法について説明する。図13は、学習済モデルの作成に関するフローチャートである。この作成方法に関する処理は、機械学習装置20の制御部21により実行される。
次に、図14を参照して、本実施形態における心臓超音波検査結果Raの推定方法について説明する。図14は、心臓超音波検査結果Raの推定に関するフローチャートである。この作成方法に関する処理は、検査結果推定装置10の制御部11により実行される。
以上、上述した実施形態は本発明を実施するための例示に過ぎない。よって、本発明は上述した実施形態に限定されることなく、その趣旨を逸脱しない範囲内で上述した実施形態を適宜変形して実施することが可能である。
Claims (8)
- 心電信号を取得する信号取得部と、
学習用心電信号を入力データとし心臓超音波検査結果を教師データとして機械学習された学習済モデルを用いて、前記信号取得部により取得された心電信号に応じた心臓超音波検査結果を推定する推定部と、
前記推定部により推定された前記心臓超音波検査結果を出力する出力部と、を備える、検査結果推定装置。 - 前記心臓超音波検査結果は、心臓の部位の寸法、心臓内の血液の流量、心臓内の血液の流速および心臓内の血液の圧力のうちの少なくとも1つの項目を含む、請求項1に記載の検査結果推定装置。
- 前記出力部は、前記心臓超音波検査結果に含まれる複数の項目が記載されたレポートを表示部に表示する、請求項1または2に記載の検査結果推定装置。
- 前記信号取得部は、心電図画像データから変換された数値データを含む心電信号を取得する、請求項1~3のいずれか1項に記載の検査結果推定装置。
- 前記出力部は、数値データを含む前記心臓超音波検査結果を出力する、請求項1~4のいずれか1項に記載の検査結果推定装置。
- 前記推定部は、前記学習済モデルを用いて、前記信号取得部により取得された心電信号に応じた、壁運動の異常の有無および先天性心疾患の有無の少なくとも一方を含む前記心臓超音波検査結果を推定する、請求項1~5のいずれか1項に記載の検査結果推定装置。
- 医療ガイドラインの情報が記憶された記憶部をさらに備え、
前記推定部は、推定した前記心臓超音波検査結果と、前記医療ガイドラインの情報とに基づいて、医師による診療を支援するための支援情報を生成し、
前記出力部は、前記推定部により推定された前記心臓超音波検査結果と、前記支援情報とを出力する、請求項1~6のいずれか1項に記載の検査結果推定装置。 - 心電信号を取得する処理と、
学習用心電信号を入力データとし心臓超音波検査結果を教師データとして機械学習された学習済モデルを用いて、前記心電信号に応じた心臓超音波検査結果を推定する処理と、
推定された前記心臓超音波検査結果を出力する処理と、コンピュータに実行させる、プログラム。
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JP2020140479A JP7152724B2 (ja) | 2020-08-21 | 2020-08-21 | 機械学習装置、プログラム、及び検査結果推定装置 |
PCT/JP2021/010688 WO2022038819A1 (ja) | 2020-08-21 | 2021-03-16 | 検査結果推定装置、プログラム及びプログラム記憶媒体 |
EP21857971.2A EP4198994A1 (en) | 2020-08-21 | 2021-03-16 | Test result estimation device, program, and program storage medium |
CN202180051576.9A CN115885347A (zh) | 2020-08-21 | 2021-03-16 | 检查结果估计装置、程序以及程序存储介质 |
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JP2002243706A (ja) * | 2001-02-09 | 2002-08-28 | Sumitomo Metal Ind Ltd | 超音波探傷方法及び装置 |
WO2018211687A1 (ja) * | 2017-05-19 | 2018-11-22 | 株式会社オプティム | コンピュータシステム、被験者診断方法及び支援プログラム |
JP2019514635A (ja) * | 2016-03-28 | 2019-06-06 | ジェンドゥ・イノベイションズ・プライベイト・リミテッドJendo Innovations (Pvt) Ltd | 血管系の健康を監視するためのシステムおよび方法 |
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JP2020520273A (ja) * | 2017-05-18 | 2020-07-09 | コーニンクレッカ フィリップス エヌ ヴェKoninklijke Philips N.V. | 時間的な心臓画像の畳み込み深層学習解析 |
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JP2020520273A (ja) * | 2017-05-18 | 2020-07-09 | コーニンクレッカ フィリップス エヌ ヴェKoninklijke Philips N.V. | 時間的な心臓画像の畳み込み深層学習解析 |
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