World's Best Scientists 2026 revealed!
Hiroshi Fujita

Hiroshi Fujita

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Computer Science
Japan
2025

D-Index & Metrics

Computer Science

D-Index
60
Citations
14801
World Ranking
3229
National Ranking
27

Research.com Recognitions

  • 2025 - Research.com Computer Science in Japan Leader Award
  • 2022 - Research.com Computer Science in Japan Leader Award

Overview

Hiroshi Fujita is affiliated with Gifu University in Japan. Their research spans multiple disciplines including medicine, engineering, and business, management, and accounting, with a focus on the intersection of technology and healthcare.

Their work involves several main fields of study:

  • Medicine
  • Engineering
  • Business, Management and Accounting

Within these broader fields, Fujita's subfields of study include:

  • Management of Technology and Innovation
  • Biochemistry
  • Genetics
  • Mechanical Engineering
  • Aerospace Engineering

Their research topics highlight a focus on blood-related medical practices and emerging technologies, including:

  • Blood donation and transfusion practices
  • Blood transfusion and management
  • Hemoglobinopathies and related disorders
  • Neurogenetic and muscular disorders research
  • Travel-related health issues
  • Trauma, hemostasis, coagulopathy, resuscitation
  • UAV applications and optimization

Frequent co-authors collaborating with Fujita include:

  • Koki Yakushiji
  • Fumiatsu Yakushiji
  • Mikio Murata
  • Asashi Tanaka
  • Makoto Okuda

Fujita's recent published papers reflect the application of unmanned aerial vehicles (UAVs) in medical contexts as well as trauma-related clinical studies:

  • Short-Range Transportation Using Unmanned Aerial Vehicles (UAVs) during Disasters in Japan, 2020, published in Drones
  • The Quality of Blood is not Affected by Drone Transport: An Evidential Study of the Unmanned Aerial Vehicle Conveyance of Transfusion Material in Japan, 2020, published in Drones
  • Quality Control of Red Blood Cell Solutions for Transfusion Transported via Drone Flight to a Remote Island, 2021, published in Drones
  • Effects of in-house cryoprecipitate on transfusion usage and mortality in patients with multiple trauma with severe traumatic brain injury: a retrospective cohort study, 2020, published in PubMed
  • Newborn screening for spinal muscular atrophy in Osaka -challenges in a Japanese pilot study-, 2023, published in Brain and Development

Their frequent publication venues indicate specialization and interest in transfusion medicine and technological applications in healthcare:

  • Japanese Journal of Transfusion and Cell Therapy
  • Hematology & Transfusion International Journal
  • Drones
  • Vox Sanguinis
  • Brain and Development

Best Publications

  • Development of a digital image database for chest radiographs with and without a lung nodule: receiver operating characteristic analysis of radiologists' detection of pulmonary nodules.

    Junji Shiraishi;Shigehiko Katsuragawa;Junpei Ikezoe;Tsuneo Matsumoto

  • A simple method for determining the modulation transfer function in digital radiography

    H. Fujita;D.-Y. Tsai;T. Itoh;K. Doi

  • Automated detection of pulmonary nodules in helical CT images based on an improved template-matching technique

    Yongbum Lee;T. Hara;H. Fujita;S. Itoh

  • Retinopathy Online Challenge: Automatic Detection of Microaneurysms in Digital Color Fundus Photographs

    Meindert Niemeijer;Bram van Ginneken;Michael J Cree;Atsushi Mizutani

  • Classification of teeth in cone-beam CT using deep convolutional neural network

    Yuma Miki;Chisako Muramatsu;Tatsuro Hayashi;Xiangrong Zhou

  • Comparing and combining algorithms for computer-aided detection of pulmonary nodules in computed tomography scans: The ANODE09 study

    Bram van Ginneken;Bram van Ginneken;Samuel G. Armato;Bartjan de Hoop;Saskia van Amelsvoort-van de Vorst

  • Evaluation of an artificial intelligence system for detecting vertical root fracture on panoramic radiography

    Motoki Fukuda;Kyoko Inamoto;Naoki Shibata;Yoshiko Ariji

  • Automated Classification of Lung Cancer Types from Cytological Images Using Deep Convolutional Neural Networks.

    Atsushi Teramoto;Tetsuya Tsukamoto;Yuka Kiriyama;Hiroshi Fujita

  • [AI-based computer-aided diagnosis (AI-CAD): The latest review to read first].

    Hiroshi Fujita

  • Automated detection of pulmonary nodules in PET/CT images: Ensemble false-positive reduction using a convolutional neural network technique.

    Atsushi Teramoto;Hiroshi Fujita;Osamu Yamamuro;Tsuneo Tamaki

  • Deep-learning classification using convolutional neural network for evaluation of maxillary sinusitis on panoramic radiography

    Makoto Murata;Yoshiko Ariji;Yasufumi Ohashi;Taisuke Kawai

  • Deep learning of the sectional appearances of 3D CT images for anatomical structure segmentation based on an FCN voting method.

    Xiangrong Zhou;Ryosuke Takayama;Song Wang;Takeshi Hara

  • Automatic detection and classification of radiolucent lesions in the mandible on panoramic radiographs using a deep learning object detection technique.

    Yoshiko Ariji;Yudai Yanashita;Syota Kutsuna;Chisako Muramatsu

  • Investigation of basic imaging properties in digital radiography. 6. MTFs of II-TV digital imaging systems

    Hiroshi Fujita;Kunio Doi;Maryellen Lissak Giger

  • Contrast-enhanced computed tomography image assessment of cervical lymph node metastasis in patients with oral cancer by using a deep learning system of artificial intelligence.

    Yoshiko Ariji;Motoki Fukuda;Yoshitaka Kise;Michihito Nozawa

  • Automated microaneurysm detection method based on double ring filter in retinal fundus images

    Atsushi Mizutani;Chisako Muramatsu;Yuji Hatanaka;Shinsuke Suemori

  • Computer-aided diagnosis: The emerging of three CAD systems induced by Japanese health care needs

    Hiroshi Fujita;Yoshikazu Uchiyama;Toshiaki Nakagawa;Daisuke Fukuoka

  • Application of artificial neural network to computer-aided diagnosis of coronary artery disease in myocardial SPECT bull's-eye images.

    Hiroshi Fujita;Tetsuro Katafuchi;Toshiisa Uehara;Tsunehiko Nishimura

  • Fast lung nodule detection in chest CT images using cylindrical nodule-enhancement filter

    Atsushi Teramoto;Hiroshi Fujita

  • Basic imaging properties of a computed radiographic system with photostimulable phosphors.

    Hiroshi Fujita;Katsuhiko Ueda;Junji Morishita;Tsuyoshi Fujikawa

  • Automatic segmentation and recognition of anatomical lung structures from high-resolution chest CT images.

    Xiangrong Zhou;Tatsuro Hayashi;Takeshi Hara;Hiroshi Fujita

Frequent Co-Authors

Kunio Doi
Kunio Doi University of Chicago
Hirotaro Mori
Hirotaro Mori Osaka University
Song Wang
Song Wang University of South Carolina
Heang Ping Chan
Heang Ping Chan University of Michigan–Ann Arbor

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