AIMC Topic: Algorithms

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Identifying the active ingredients of carbonized Typhae Pollen by spectrum-effect relationship combined with MBPLS, PLS, and SVM algorithms.

Journal of pharmaceutical and biomedical analysis
Typhae Pollen (TP) and its carbonized product (carbonized Typhae Pollen, CTP), as cut-and-dried herbal drugs, have been widely used in the form of slices in clinical settings. However, the two drugs exhibit a great difference in terms of their clinic...

Affine image registration of arterial spin labeling MRI using deep learning networks.

NeuroImage
Convolutional neural networks (CNN) have demonstrated good accuracy and speed in spatially registering high signal-to-noise ratio (SNR) structural magnetic resonance imaging (sMRI) images. However, some functional magnetic resonance imaging (fMRI) im...

Bias in artificial intelligence in vascular surgery.

Seminars in vascular surgery
Application of artificial intelligence (AI) has revolutionized the utilization of big data, especially in patient care. The potential of deep learning models to learn without a priori assumption, or without prior learning, to connect seemingly unrela...

Deep Learning Algorithm for Tumor Segmentation and Discrimination of Clinically Significant Cancer in Patients with Prostate Cancer.

Current oncology (Toronto, Ont.)
BACKGROUND: We investigated the feasibility of a deep learning algorithm (DLA) based on apparent diffusion coefficient (ADC) maps for the segmentation and discrimination of clinically significant cancer (CSC, Gleason score ≥ 7) from non-CSC in patien...

Machine learning prediction and classification of behavioral selection in a canine olfactory detection program.

Scientific reports
There is growing interest in canine behavioral research specifically for working dogs. Here we take advantage of a dataset of a Transportation Safety Administration olfactory detection cohort of 628 Labrador Retrievers to perform Machine Learning (ML...

AIVariant: a deep learning-based somatic variant detector for highly contaminated tumor samples.

Experimental & molecular medicine
The detection of somatic DNA variants in tumor samples with low tumor purity or sequencing depth remains a daunting challenge despite numerous attempts to address this problem. In this study, we constructed a substantially extended set of actual posi...

FDU-Net: Deep Learning-Based Three-Dimensional Diffuse Optical Image Reconstruction.

IEEE transactions on medical imaging
Near-infrared diffuse optical tomography (DOT) is a promising functional modality for breast cancer imaging; however, the clinical translation of DOT is hampered by technical limitations. Specifically, conventional finite element method (FEM)-based o...

Deep learning applications in visual data for benign and malignant hematologic conditions: a systematic review and visual glossary.

Haematologica
Deep learning (DL) is a subdomain of artificial intelligence algorithms capable of automatically evaluating subtle graphical features to make highly accurate predictions, which was recently popularized in multiple imaging-related tasks. Because of it...

Psychological AI: Designing Algorithms Informed by Human Psychology.

Perspectives on psychological science : a journal of the Association for Psychological Science
Psychological artificial intelligence (AI) applies insights from psychology to design computer algorithms. Its core domain is decision-making under uncertainty, that is, ill-defined situations that can change in unexpected ways rather than well-defin...

Genomics and Artificial Intelligence: Prostate Cancer.

The Urologic clinics of North America
Artificial intelligence (AI) is revolutionizing prostate cancer genomics research. By leveraging machine learning and deep learning algorithms, researchers can rapidly analyze vast genomic datasets to identify patterns and correlations that may be mi...