Hirotaka Ikeda, Yoshiharu Ohno, Kaori Yamamoto, Kazuhiro Murayama, Masato Ikedo, Masao Yui, Yunosuke Kumazawa, Yurika Shimamura, Yui Takagi, Yuhei Nakagaki, Satomu Hanamatsu, Yuki Obama, Takahiro Ueda, Hiroyuki Nagata, Yoshiyuki Ozawa, Akiyoshi Iwase, Hiroshi Toyama
Deep Learning Reconstruction for DWIs by EPI and FASE Sequences for Head and Neck Tumors
Cancers
research work focuses evaluating development threestep digitization approach designed transform traditional lectures engaging digital learning experiences aimed offering easytouse solution educators approach addresses pressing challenges modern educational environments enhancing accessibility engagement effectiveness learning digital meansquantitative analysis demonstrated notable increase knowledge gain students engaged digital format t230 2795 p 0006 traditional methods additionally observed online setting significantly improved concentration levels t230 5801 p 001 reduced distractions t230 2848 p 0005 emotional assessments based achievement emotions questionnaire aeq indicated elevation enjoyment t230 4717 p 001 reduction anxiety t230 9446 p 001 within digital learning environment substantial preference digital course format expressed 610 participants 714 acknowledging superior efficiency compared 143 traditional lecturesqualitative feedback underscored digital formats flexibility comprehensive learning experience immediate feedback key benefits nevertheless nuances preferred understanding facetoface interactions absence social component digital settings notedto conclude findings study illuminate significant advantages threestep digitization approach meeting contemporary educational challenges facilitating enhanced knowledge acquisition fostering supportive emotional climate approach signifies promising direction future medical education beyond fusing convenience digital solutions depth engagement traditional learning methodologies