AIMC Topic: Machine Learning

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Artificial intelligence in the experimental determination and prediction of macromolecular structures.

Current opinion in structural biology
Machine learning methods, in particular convolutional neural networks, have been applied to a variety of problems in cryo-EM and macromolecular crystallographic structure solution. However, they still have only limited acceptance by the community, ma...

A Combinatorial Optimization Framework for Scoring Students in University Admissions.

Evaluation review
BACKGROUND AND OBJECTIVES: Selecting applications for college admission is critical for university operation and development. This paper leverages machine learning techniques to support enrollment management teams through data-informed decision-makin...

Label-Free Differentiation of Cancer and Non-Cancer Cells Based on Machine-Learning-Algorithm-Assisted Fast Raman Imaging.

Biosensors
This paper proposes a rapid, label-free, and non-invasive approach for identifying murine cancer cells (B16F10 melanoma cancer cells) from non-cancer cells (C2C12 muscle cells) using machine-learning-assisted Raman spectroscopic imaging. Through quic...

Comparative performance analysis of K-nearest neighbour (KNN) algorithm and its different variants for disease prediction.

Scientific reports
Disease risk prediction is a rising challenge in the medical domain. Researchers have widely used machine learning algorithms to solve this challenge. The k-nearest neighbour (KNN) algorithm is the most frequently used among the wide range of machine...

Discovery of moiety preference by Shapley value in protein kinase family using random forest models.

BMC bioinformatics
BACKGROUND: Human protein kinases play important roles in cancers, are highly co-regulated by kinase families rather than a single kinase, and complementarily regulate signaling pathways. Even though there are > 100,000 protein kinase inhibitors, onl...

A Novel Approach for Feature Selection and Classification of Diabetes Mellitus: Machine Learning Methods.

Computational intelligence and neuroscience
An active research area where the experts from the medical field are trying to envisage the problem with more accuracy is diabetes prediction. Surveys conducted by WHO have shown a remarkable increase in the diabetic patients. Diabetes generally rema...

Real-Time Twitter Spam Detection and Sentiment Analysis using Machine Learning and Deep Learning Techniques.

Computational intelligence and neuroscience
In this modern world, we are accustomed to a constant stream of data. Major social media sites like Twitter, Facebook, or Quora face a huge dilemma as a lot of these sites fall victim to spam accounts. These accounts are made to trap unsuspecting gen...

Natural language processing of admission notes to predict severe maternal morbidity during the delivery encounter.

American journal of obstetrics and gynecology
BACKGROUND: Severe maternal morbidity and mortality remain public health priorities in the United States, given their high rates relative to other high-income countries and the notable racial and ethnic disparities that exist. In general, accurate ri...

Comparison of machine learning approaches for radioisotope identification using NaI(TI) gamma-ray spectrum.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
This research aims at comparing the performance of different machine learning algorithms used for NaI(TI) gamma-ray detector based radioisotope identification. Six machine learning algorithms were implemented, including support vector machine (SVM), ...

Semantic projection recovers rich human knowledge of multiple object features from word embeddings.

Nature human behaviour
How is knowledge about word meaning represented in the mental lexicon? Current computational models infer word meanings from lexical co-occurrence patterns. They learn to represent words as vectors in a multidimensional space, wherein words that are ...