Jove
Visualize
お問い合わせ
JoVE
x logofacebook logolinkedin logoyoutube logo
JoVEについて
概要リーダーシップブログJoVEヘルプセンター
著者向け
出版プロセス編集委員会範囲と方針査読よくある質問投稿
図書館員向け
推薦の声購読アクセスリソース図書館諮問委員会よくある質問
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experimentsアーカイブ
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教員リソースセンター教員サイト
利用規約
プライバシーポリシー
ポリシー

関連する概念動画

Reclosers and Fuses01:26

Reclosers and Fuses

459
Automatic circuit reclosers enhance the protection of distribution circuits by interrupting and auto-reclosing an AC circuit according to a preset sequence. They effectively manage temporary faults on overhead distribution lines, often caused by tree limbs or wildlife, by briefly disrupting service to improve overall reliability. However, contact with reclosers or energized broken conductors on the ground can pose serious hazards.
A comprehensive protection scheme for radial distribution...
459
Encoding01:19

Encoding

770
Information enters the brain through encoding, which is the input of information into the memory system. Once sensory information is received from the environment, the brain labels or codes it. The information is then organized with similar information and connected to existing concepts. Encoding occurs through automatic processing and effortful processing.
Automatic processing involves the encoding of details like time, space, frequency, and the meaning of words, usually done without conscious...
770
Circuit Breaker and Fuse Selection01:23

Circuit Breaker and Fuse Selection

579
A circuit breaker is a device engineered to interrupt fault currents and sometimes reclose automatically. When a fault current is detected, the breaker separates the electrical contacts, which generates an arc. This arc is extinguished by methods such as elongation, cooling, or splitting, depending on the breaker's design. Breakers are categorized based on the voltage they operate at and the medium used for arc extinction, such as air, oil, SF6 gas, or vacuum.
In high-voltage systems,...
579
Classification of Titrimetric Analysis Based on Reaction Types01:01

Classification of Titrimetric Analysis Based on Reaction Types

1.5K
Titrimetric analysis in solution chemistry involves measuring the volume of solutions and is often called volumetric analysis. The standard solution of known concentration in the burette is called the titrant, whereas the solution of unknown concentration in the flask is called the analyte, or titrand. Titrimetric analyses can be classified into four types based on the reactions between the titrant and analyte.
Titrations between an acid and a base lead to neutralization reactions that form...
1.5K
Cardiovascular Drugs: Classification based on Therapeutic Indications01:18

Cardiovascular Drugs: Classification based on Therapeutic Indications

4.1K
Cardiovascular diseases, encompassing a range of conditions, can significantly affect the heart's operations and the overall circulatory system. These conditions impair the heart's ability to pump blood, leading to a deficit in oxygen supply to crucial organs. Anomalies in the heart's electrical system, known as arrhythmias, can cause heartbeats to accelerate or slow down. Usually, heart rates increase during physical activity and decrease while resting or sleeping. However,...
4.1K
Machines01:19

Machines

559
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. One example of a machine is the cutting plier, which is used to cut wires by applying forces to its handles. When equal and opposite forces are exerted on the handles of the cutting plier, they cause the cutting edges to come together and apply equal and opposite reaction forces on the wire, which are greater than the applied forces.
A free-body diagram of the...
559

こちらも読む

関連記事

共著者、ジャーナル、引用グラフによってこの研究に関連する記事。

並び替え
Same author

Low-molecular-weight polysaccharide and polyol impregnation enhances the rehydration recovery capacity of freeze-dried potato slices.

Food chemistry: X·2026
Same author

The NAC Transcription Factor SlNAP2 Enhances Tomato Resistance to Ralstonia solanacearum.

Physiologia plantarum·2026
Same author

Corrigendum to "Oleanolic acid 28-O-β-D-glucopyranoside alleviates TNBS-induced ulcerative colitis in rat by regulating Nrf2/x-CT/GPX4-mediated ferroptosis" [Journal of Ethnopharmacology 353 (2025) 120369].

Journal of ethnopharmacology·2026
Same author

Targeting barrier integrity: Pseudoginsenoside RT2 ameliorates ulcerative colitis by driving epithelial renewal via the Wnt/β-catenin pathway.

Phytomedicine : international journal of phytotherapy and phytopharmacology·2026
Same author

Elevating RNA m<sup>5</sup>C methylation provides a promising strategy for crop productivity.

National science review·2026
Same author

Hydroxypropylated/oxidized starch-based regulation of the potato-barley system for extrusion-based 3D food printing.

International journal of biological macromolecules·2026

関連する実験動画

Updated: Jan 23, 2026

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

2.5K

膀胱病変の融合3D CT放射線画像と3Dオートエンコーダー深層特徴を用いた機械学習ベースのマルチクラス分類

Hongwei Xiao1,2, Weihao Liu3, Huancheng Yang1

  • 1Department of Radiology, The Third Affiliated Hospital of Shenzhen University (Luohu People's Hospital), No. 47 Youyi Road, Luohu District, Shenzhen, Guangdong 518000, China.

European journal of radiology open
|January 22, 2026
PubMed
まとめ

本研究は、膀胱病変分類のためのハイブリッド放射線画像と深層学習を用いた自動CTスキャン解析フレームワークを提示する。このシステムは、正常な膀胱、結石、癌、膀胱炎を正確に特定し、臨床診断を支援する。

キーワード:
膀胱癌結石膀胱炎ハイブリッド特徴融合機械学習

さらに関連する動画

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
09:34

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

Published on: September 25, 2021

4.5K
Deep Learning-Based Segmentation of Cryo-Electron Tomograms
10:25

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Published on: November 11, 2022

10.6K

関連する実験動画

Last Updated: Jan 23, 2026

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

2.5K
A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
09:34

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

Published on: September 25, 2021

4.5K
Deep Learning-Based Segmentation of Cryo-Electron Tomograms
10:25

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Published on: November 11, 2022

10.6K

科学分野:

  • 放射線医学
  • 人工知能
  • 医用画像解析

背景:

  • 非造影CTからの膀胱病変の正確なマルチクラス分類は、タイムリーな診断と治療のために重要です。
  • 現在の方法では、効率的な臨床統合に必要な精度と自動化が不足している可能性があります。

主な方法:

  • 902件のCTスキャンに対する後向き分析が実施されました。
  • 統合パイプラインには、自動膀胱セグメンテーション(3D-UNet)、ハイブリッド特徴抽出(放射線画像+深層学習)、特徴選択(LASSO)、および分類(XGBoost)が含まれていました。
  • パフォーマンスは、one-vs-rest戦略とクロスバリデーションを使用したAUROCで評価されました。

結論:

  • ハイブリッドCT解析フレームワークは、自動マルチクラス膀胱病変分類において臨床的に関連性の高いパフォーマンスを示しました。
  • 放射線画像特徴と深層特徴の補完的な役割は、解釈可能な診断補助を提供します。
  • このフレームワークは、鑑別診断を支援するために臨床ワークフローに統合される可能性を示しています。