AIMC Topic: Algorithms

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A Question-and-Answer System to Extract Data From Free-Text Oncological Pathology Reports (CancerBERT Network): Development Study.

Journal of medical Internet research
BACKGROUND: Information in pathology reports is critical for cancer care. Natural language processing (NLP) systems used to extract information from pathology reports are often narrow in scope or require extensive tuning. Consequently, there is growi...

[Artificial Intelligence: Challenges and Applications in Intensive Care Medicine].

Anasthesiologie, Intensivmedizin, Notfallmedizin, Schmerztherapie : AINS
The high workload in intensive care medicine arises from the exponential growth of medical knowledge, the flood of data generated by the permanent and intensive monitoring of intensive care patients, and the documentation burden. Artificial intellige...

[Usage of Artificial Intelligence in the Combat against the COVID-19 Pandemic].

Anasthesiologie, Intensivmedizin, Notfallmedizin, Schmerztherapie : AINS
The COVID-19 pandemic is a global health emergency of historic dimension. In this situation, researchers worldwide wanted to help manage the pandemic by using artificial intelligence (AI). This narrative review aims to describe the usage of AI in the...

[Artificial Intelligence: Infrastructures and Prerequisites at European Level].

Anasthesiologie, Intensivmedizin, Notfallmedizin, Schmerztherapie : AINS
The application of artificial intelligence (AI) is often associated with the use of large amounts of data for the construction of AI models and algorithms. This data should ideally comply with the FAIR Data principles, i.e. being findable, accessible...

Diagnosis of Early Cervical Cancer with a Multimodal Magnetic Resonance Image under the Artificial Intelligence Algorithm.

Contrast media & molecular imaging
This research was conducted to explore the value of multimodal magnetic resonance imaging (MRI) based on the alternating direction algorithm in the diagnosis of early cervical cancer. 64 patients diagnosed with early cervical cancer clinicopathologic...

Three-Dimensional Ultrasound Images in the Assessment of Bladder Tumor Health Monitoring under Deep Learning Algorithms.

Computational and mathematical methods in medicine
This study was aimed at exploring the application value of three-dimensional (3D) ultrasound based on deep learning and continued nursing health monitoring (CNHM) mode in promoting the recovery of bladder cancer patients after surgery. 60 patients wh...

Investigation of Effectiveness of Shuffled Frog-Leaping Optimizer in Training a Convolution Neural Network.

Journal of healthcare engineering
One of the leading algorithms and architectures in deep learning is Convolution Neural Network (CNN). It represents a unique method for image processing, object detection, and classification. CNN has shown to be an efficient approach in the machine l...

Scalable deep learning algorithm to compute percent pulmonary contusion among patients with rib fractures.

The journal of trauma and acute care surgery
BACKGROUND: Pulmonary contusion exists along a spectrum of severity, yet is commonly binarily classified as present or absent. We aimed to develop a deep learning algorithm to automate percent pulmonary contusion computation and exemplify how transfe...

Early identification of ICU patients at risk of complications: Regularization based on robustness and stability of explanations.

Artificial intelligence in medicine
The aim of this study is to build machine learning models to predict severe complications using administrative and clinical elements that are collected immediately after patient admission to the intensive care unit (ICU). Risk models are of increasin...

Low-precision feature selection on microarray data: an information theoretic approach.

Medical & biological engineering & computing
The number of interconnected devices, such as personal wearables, cars, and smart-homes, surrounding us every day has recently increased. The Internet of Things devices monitor many processes, and have the capacity of using machine learning models fo...