Year 2023

• Enhancing Renal Tumor Detection: Leveraging Artificial Neural Networks in Computed Tomography Analysis

  Publication

  • M. Glembin
  • A. Obuchowski
  • B. Klaudel
  • B. Rydziński
  • R. Karski
  • P. Syty
  • P. Jasik
  • W. J. Narożański

  - Medical Science Monitor - Year 2023

  Renal cell carcinoma is one of the most common cancers in Europe, with a total incidence rate of 18.4 cases per 100 000 population. There is currently significant overdiagnosis (11% to 30.9%) at times of planned surgery based on radiological studies. The purpose of this study was to create an artificial neural network (ANN) solution based on computed tomography (CT) images as an additional tool to improve the differentiation of...

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Year 2022

• ColorNephroNet: Kidney tumor malignancy prediction using medical image colorization

  Publication

  • A. Obuchowski
  • B. Klaudel
  • R. Karski
  • B. Rydziński
  • M. Glembin
  • P. Syty
  • P. Jasik

  - Proceedings of FLAIRS-35 - Year 2022

  Renal tumor malignancy classification is one of the crucial tasks in urology, being a primary factor included in the decision of whether to perform kidney removal surgery (nephrectomy) or not. Currently, tumor malignancy prediction is determined by the radiological diagnosis based on computed tomography (CT) images. However, it is estimated that up to 16% of nephrectomies could have been avoided because the tumor that had been...

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• COVID-19 severity forecast based on machine learning and complete blood count data

  Publication

  • B. Klaudel
  • A. Obuchowski
  • R. Karski
  • B. Rydziński
  • P. Jasik
  • Z. Kowalczuk

  - Year 2022

  Proper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...

  Full text to download in external service

• COVID-19 severity forecast based on machine learning and complete blood count data

  Publication

  • B. Klaudel
  • A. Obuchowski
  • R. Karski
  • B. Rydziński
  • P. Jasik
  • Z. Kowalczuk

  - Year 2022

  Proper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...

  Full text to download in external service