AIMC Topic: Algorithms

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The PHU-NET: A robust phase unwrapping method for MRI based on deep learning.

Magnetic resonance in medicine
PURPOSE: This work was aimed at designing a deep-learning-based approach for MR image phase unwrapping to improve the robustness and efficiency of traditional methods.

B-Map: a fuzzy-based model to detect foreign objects in a brain.

Medical & biological engineering & computing
To cope up with the medical complications, scientists and physicians rely more on digitized historical evidence. It helps them to identify the disease and to develop new drugs and strategies. The authors have designed a model called B-Map. It can det...

Skin Cancer Detection Using Kernel Fuzzy C-Means and Improved Neural Network Optimization Algorithm.

Computational intelligence and neuroscience
Early diagnosis of malignant skin cancer from images is a significant part of the cancer treatment process. One of the principal purposes of this research is to propose a pipeline methodology for an optimum computer-aided diagnosis of skin cancers. T...

Optimized adaptive Savitzky-Golay filtering algorithm based on deep learning network for absorption spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
An improved Savitzky-Golay (S-G) filtering algorithm was developed to denoise the absorption spectroscopy of nitrogen oxide (NO). A deep learning (DL) network was introduced to the traditional S-G filtering algorithm to adjust the window size and pol...

Identifying mislabelled samples: Machine learning models exceed human performance.

Annals of clinical biochemistry
BACKGROUND: It is difficult for clinical laboratories to identify samples that are labelled with the details of an incorrect patient. Many laboratories screen for these errors with delta checks, with final decision-making based on manual review of re...

PyRMD: A New Fully Automated AI-Powered Ligand-Based Virtual Screening Tool.

Journal of chemical information and modeling
Artificial intelligence (AI) algorithms are dramatically redefining the current drug discovery landscape by boosting the efficiency of its various steps. Still, their implementation often requires a certain level of expertise in AI paradigms and codi...

Contrast-enhanced to noncontrast CT transformation via an adjacency content-transfer-based deep subtraction residual neural network.

Physics in medicine and biology
To reduce overall patient radiation exposure in some clinical scenarios (since cancer patients need frequent follow-ups), noncontrast CT is not used in some institutions. However, although less desirable, noncontrast CT could provide additional impor...

Challenges in Obtaining Valid Causal Effect Estimates with Machine Learning Algorithms.

American journal of epidemiology
Unlike parametric regression, machine learning (ML) methods do not generally require precise knowledge of the true data generating mechanisms. As such, numerous authors have advocated for ML methods to estimate causal effects. Unfortunately, ML algor...