Risk of Invalidation of Data in Hospital Information Systems in Indonesia

Binsar, Faisal; Eryanto, Ery; Wahyudi, Indra; Sugandi, Yovin; Suroso, Jarot S.

doi:10.1109/icimtech50083.2020.9211200

Cited by 6 publications

(1 citation statement)

References 11 publications

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“…In addition, considering that the diagnosis of MRI images is highly subjective and mostly depends on the experience and professional knowledge of doctors, the lack of talents in this field is also a major reason for the low efficiency of diagnoses [ 21 ]. The low recognition rate of early diagnosis leads to more difficult later-stage treatment, forming a vicious circle [ 22 , 23 ]. In China, 80% of medical resources are concentrated in large cities with only 10% of the population.…”

Section: Introductionmentioning

confidence: 99%

AI-Assisted Diagnosis and Decision-Making Method in Developing Countries for Osteosarcoma

Tang

Huang

et al. 2022

Healthcare

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Osteosarcoma is a malignant tumor derived from primitive osteogenic mesenchymal cells, which is extremely harmful to the human body and has a high mortality rate. Early diagnosis and treatment of this disease is necessary to improve the survival rate of patients, and MRI is an effective tool for detecting osteosarcoma. However, due to the complex structure and variable location of osteosarcoma, cancer cells are highly heterogeneous and prone to aggregation and overlap, making it easy for doctors to inaccurately predict the area of the lesion. In addition, in developing countries lacking professional medical systems, doctors need to examine mass of osteosarcoma MRI images of patients, which is time-consuming and inefficient, and may result in misjudgment and omission. For the sake of reducing labor cost and improve detection efficiency, this paper proposes an Attention Condenser-based MRI image segmentation system for osteosarcoma (OMSAS), which can help physicians quickly locate the lesion area and achieve accurate segmentation of the osteosarcoma tumor region. Using the idea of AttendSeg, we constructed an Attention Condenser-based residual structure network (ACRNet), which greatly reduces the complexity of the structure and enables smaller hardware requirements while ensuring the accuracy of image segmentation. The model was tested on more than 4000 samples from two hospitals in China. The experimental results demonstrate that our model has higher efficiency, higher accuracy and lighter structure for osteosarcoma MRI image segmentation compared to other existing models.

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Section: Introductionmentioning

confidence: 99%

AI-Assisted Diagnosis and Decision-Making Method in Developing Countries for Osteosarcoma

Tang

Huang

et al. 2022

Healthcare

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Management Information System for Lancang Kuning Hospital Dompet Dhuafa Pekanbaru Using Codeigniter Framework

Ismainar¹,

Melyanti²,

Yulisman³

et al. 2021

J. Phys.: Conf. Ser.

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The very rapid development of technology creates many technological products, especially in the field of Information and Communication Technology (ICT). The development of ICT in the world is increasingly widespread, where the use of ICT is not limited to the trade sector, but in other fields, such as government. The Clinical Management Information System is a form of technological development aimed at clinics in order to manage clinical management data in an integrated electronic reporting information system. To make it happen, a system was created that could manage patient medical record data so as not to wait long. The system also contains drug data, doctor data, employee data, action data and cashier bills. The method used in the development of this system is the waterfall method. It is hoped that the construction of this system can help facilitate clinical service staff in patient data, drug data, doctor data, employee data, action data and cashier bills.

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The Borrowing Medical Records System : A Case Study of Medical Information System

Boonkleang,

Supapong,

Rujivorakul

2023

2023 Joint International Conference on Digital Arts, Media and Technology With ECTI Northern Section Conference on Electrical,

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Risk of Invalidation of Data in Hospital Information Systems in Indonesia

Cited by 6 publications

References 11 publications

AI-Assisted Diagnosis and Decision-Making Method in Developing Countries for Osteosarcoma

AI-Assisted Diagnosis and Decision-Making Method in Developing Countries for Osteosarcoma

Management Information System for Lancang Kuning Hospital Dompet Dhuafa Pekanbaru Using Codeigniter Framework

The Borrowing Medical Records System : A Case Study of Medical Information System

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