AIMC Topic: Machine Learning

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A Deep Learning Approach to Antibiotic Discovery.

Cell
Due to the rapid emergence of antibiotic-resistant bacteria, there is a growing need to discover new antibiotics. To address this challenge, we trained a deep neural network capable of predicting molecules with antibacterial activity. We performed pr...

Deep-learning with synthetic data enables automated picking of cryo-EM particle images of biological macromolecules.

Bioinformatics (Oxford, England)
MOTIVATION: Single-particle cryo-electron microscopy (cryo-EM) has become a powerful technique for determining 3D structures of biological macromolecules at near-atomic resolution. However, this approach requires picking huge numbers of macromolecula...

[Artificial intelligence in Danish healthcare].

Ugeskrift for laeger
Artificial intelligence (AI) and machine learning have become important in medicine as shown in this review. Automatic tools can be trained to analyse patient data and thereby be a great asset to doctors when diagnosing and treating patients. Denmark...

Research Progress and Prospect of Machine Learning in Bone Age Assessment.

Fa yi xue za zhi
Bone age assessment has always been one of the key issues and difficulties in forensic science. With the gradual development of machine learning in many industries, it has been widely introduced to imageology, genomics, oncology, pathology, surgery a...

Determination of Electrocution Using Fourier Transform Infrared Microspectroscopy and Machine Learning Algorithm.

Fa yi xue za zhi
Objective To analyze the differences among electrical damage, burns and abrasions in pig skin using Fourier transform infrared microspectroscopy (FTIR-MSP) combined with machine learning algorithm, to construct three kinds of skin injury determinatio...

In vitro monitoring of photoinduced necrosis in HeLa cells using digital holographic microscopy and machine learning.

Journal of the Optical Society of America. A, Optics, image science, and vision
Digital holographic microscopy supplemented with the developed cell segmentation and machine learning and classification algorithms is implemented for quantitative description of the dynamics of cellular necrosis induced by photodynamic treatment in ...

Retrospective imaging studies of gastric cancer: Study protocol clinical trial (SPIRIT Compliant).

Medicine
INTRODUCTION: Peritoneal metastasis (PM) is a frequent condition in patients presenting with gastric cancer, especially in younger patients with advanced tumor stages. Computer tomography (CT) is the most common noninvasive modality for preoperative ...

Quantitative scoring of epithelial and mesenchymal qualities of cancer cells using machine learning and quantitative phase imaging.

Journal of biomedical optics
SIGNIFICANCE: We introduce an application of machine learning trained on optical phase features of epithelial and mesenchymal cells to grade cancer cells' morphologies, relevant to evaluation of cancer phenotype in screening assays and clinical biops...