AIMC Topic: Algorithms

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Machine-learning Algorithms for Ischemic Heart Disease Prediction: A Systematic Review.

Current cardiology reviews
PURPOSE: This review aims to summarize and evaluate the most accurate machinelearning algorithm used to predict ischemic heart disease.

Accounting Conformational Dynamics into Structural Modeling Reflected by Cryo-EM with Deep Learning.

Combinatorial chemistry & high throughput screening
With the continuous development of structural biology, the requirement for accurate threedimensional structures during functional modulation of biological macromolecules is increasing. Therefore, determining the dynamic structures of bio-macromolecul...

Comparative Analysis Between Machine Learning Algorithms and Conventional Regression in Predicting the Prognosis of Patients with Basilar Invagination: A Retrospective Cohort Study.

Turkish neurosurgery
AIM: To identify predictors of basilar invagination (BI) prognosis and compare diagnostic properties between logistic modeling and machine learning methods.

Deep learning under mass-to-charge ratio pre-retrieval to realize electron ionization mass spectrometry library retrieval.

Rapid communications in mass spectrometry : RCM
RATIONALE: Gas chromatography-mass spectrometry (GC-MS) is an analytical technique widely used in materials science, biomedicine, and other fields. The target compound in the experiment is identified by searching for its mass spectrum in a large mass...

[Single-channel electroencephalogram signal used for sleep state recognition based on one-dimensional width kernel convolutional neural networks and long-short-term memory networks].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Aiming at the problem that the unbalanced distribution of data in sleep electroencephalogram(EEG) signals and poor comfort in the process of polysomnography information collection will reduce the model's classification ability, this paper proposed a ...

[A deep-learning model for the assessment of coronary heart disease and related risk factors via the evaluation of retinal fundus photographs].

Zhonghua xin xue guan bing za zhi
To develop and validate a deep learning model based on fundus photos for the identification of coronary heart disease (CHD) and associated risk factors. Subjects aged>18 years with complete clinical examination data from 149 hospitals and medical e...

Applying Image-Based Food-Recognition Systems on Dietary Assessment: A Systematic Review.

Advances in nutrition (Bethesda, Md.)
Dietary assessment can be crucial for the overall well-being of humans and, at least in some instances, for the prevention and management of chronic, life-threatening diseases. Recall and manual record-keeping methods for food-intake monitoring are a...

Artificial intelligence in breast cancer diagnostics.

Cell reports. Medicine
Since breast cancer deaths are mainly due to metastasis, predicting the risk that a primary tumor will develop metastasis after a first diagnosis is a central issue that could be addressed by artificial intelligence. To overcome the problem posed by ...

Transition state search and geometry relaxation throughout chemical compound space with quantum machine learning.

The Journal of chemical physics
We use energies and forces predicted within response operator based quantum machine learning (OQML) to perform geometry optimization and transition state search calculations with legacy optimizers but without the need for subsequent re-optimization w...