Literature DB >> 10719499

Designing and implementing the transition to a fully digital hospital.

S A Pavlopoulos1, A N Delopoulos.   

Abstract

The increase in the number of examinations performed in modern healthcare institutions in conjunction with the range of imaging modalities available today have resulted in a tremendous increase in the number of medical images generated and has made the need for a dedicated system able to acquire, distribute, and store medical image data very attractive. Within the framework of the Hellenic R&D program, we have designed and implemented a picture archiving and communication system for a high-tech cardiosurgery hospital in Greece. The system is able to handle in a digital form images produced from ultrasound, X-ray angiography, gamma-camera, chest X-rays, as well as electrocardiogram signals. Based on the adoption of an open architecture highly relying on the DICOM standard, the system enables the smooth transition from the existing procedures to a fully digital operation mode and the integration of all existing medical equipment to the new central archiving system.

Entities:  

Mesh:

Year:  1999        PMID: 10719499     DOI: 10.1109/4233.748971

Source DB:  PubMed          Journal:  IEEE Trans Inf Technol Biomed        ISSN: 1089-7771


  7 in total

1.  System integration and DICOM image creation for PET-MR fusion.

Authors:  Chia-Hung Hsiao; Tsair Kao; Yu-Hua Fang; Jiunn-Kuen Wang; Wan-Yuo Guo; Liang-Hsiao Chao; Sang-Hue Yen
Journal:  J Digit Imaging       Date:  2005-03       Impact factor: 4.056

2.  Developing a medical image content repository for e-learning.

Authors:  Chia-Hung Hsiao; Tien-Cheng Hsu; Jing Ning Chang; Stephen J H Yang; Shuenn-Tsong Young; Woei Chyn Chu
Journal:  J Digit Imaging       Date:  2006-09       Impact factor: 4.056

3.  Outpatient clinic: where is the delay?

Authors:  H R H Patel; C N Luxman; T S Bailey; J D M Brunning; D Zemmel; L K Morrell; M S Nathan; R A Miller
Journal:  J R Soc Med       Date:  2002-12       Impact factor: 5.344

4.  Predicting Characteristics Associated with Breast Cancer Survival Using Multiple Machine Learning Approaches.

Authors:  Mohammad Nazmul Haque; Tahia Tazin; Mohammad Monirujjaman Khan; Shahla Faisal; Sobhee Md Ibraheem; Haneen Algethami; Faris A Almalki
Journal:  Comput Math Methods Med       Date:  2022-04-25       Impact factor: 2.809

5.  Machine Learning Based Comparative Analysis for Breast Cancer Prediction.

Authors:  Mohammad Monirujjaman Khan; Somayea Islam; Srobani Sarkar; Foyazel Iben Ayaz; Morsaleen Kabeer Ananda; Tahia Tazin; Amani Abdulrahman Albraikan; Faris A Almalki
Journal:  J Healthc Eng       Date:  2022-04-11       Impact factor: 3.822

6.  The Efficacy of Machine-Learning-Supported Smart System for Heart Disease Prediction.

Authors:  Nurul Absar; Emon Kumar Das; Shamsun Nahar Shoma; Mayeen Uddin Khandaker; Mahadi Hasan Miraz; M R I Faruque; Nissren Tamam; Abdelmoneim Sulieman; Refat Khan Pathan
Journal:  Healthcare (Basel)       Date:  2022-06-18

Review 7.  Artificial intelligence, machine learning, computer-aided diagnosis, and radiomics: advances in imaging towards to precision medicine.

Authors:  Marcel Koenigkam Santos; José Raniery Ferreira Júnior; Danilo Tadao Wada; Ariane Priscilla Magalhães Tenório; Marcello Henrique Nogueira Barbosa; Paulo Mazzoncini de Azevedo Marques
Journal:  Radiol Bras       Date:  2019 Nov-Dec
  7 in total

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