AIMC Topic: Machine Learning

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Time-range based sequential mining for survival prediction in prostate cancer.

Journal of biomedical informatics
BACKGROUND AND OBJECTIVE: Metastatic prostate cancer has a higher mortality rate than localized cancers. There is a need to investigate the survival outcome of metastatic prostate cancers separately. Also, the treatments undertaken by the patients af...

Cone-beam computed tomography-based radiomics in prostate cancer: a mono-institutional study.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
PURPOSE: The purpose of the reported study was to investigate the value of cone-beam computed tomography (CBCT)-based radiomics for risk stratification and prediction of biochemical relapse in prostate cancer.

Use of Steroid Profiling Combined With Machine Learning for Identification and Subtype Classification in Primary Aldosteronism.

JAMA network open
IMPORTANCE: Most patients with primary aldosteronism, a major cause of secondary hypertension, are not identified or appropriately treated because of difficulties in diagnosis and subtype classification. Applications of artificial intelligence combin...

Adoption of Machine Learning in Intelligent Terrain Classification of Hyperspectral Remote Sensing Images.

Computational intelligence and neuroscience
To overcome the difficulty of automating and intelligently classifying the ground features in remote-sensing hyperspectral images, machine learning methods are gradually introduced into the process of remote-sensing imaging. First, the PaviaU, Botswa...

Commentary: Dabblers: Beware of hidden dangers in machine-learning comparisons.

The Journal of thoracic and cardiovascular surgery
CENTRAL MESSAGE: Machine learning is not for dabblers. An underappreciated problem is imbalance between number of events and non-events, for which traditional C-statistics is an inappropriate evaluation metric. Characters + spaces: 193/200

Parallelograms revisited: Exploring the limitations of vector space models for simple analogies.

Cognition
Classic psychological theories have demonstrated the power and limitations of spatial representations, providing geometric tools for reasoning about the similarity of objects and showing that human intuitions sometimes violate the constraints of geom...

Pathway-Guided Deep Neural Network toward Interpretable and Predictive Modeling of Drug Sensitivity.

Journal of chemical information and modeling
To efficiently save cost and reduce risk in drug research and development, there is a pressing demand to develop methods to predict drug sensitivity to cancer cells. With the exponentially increasing number of multi-omics data derived from high-thro...

Frequency spectra characterization of noncoding human genomic sequences.

Genes & genomics
BACKGROUND: Noncoding sequences have been demonstrated to possess regulatory functions. Its classification is challenging because they do not show well-defined nucleotide patterns that can correlate with their biological functions. Genomic signal pro...

Does including machine learning predictions in ALS clinical trial analysis improve statistical power?

Annals of clinical and translational neurology
OBJECTIVE: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease which leads to progressive muscle weakness and eventually death. The increasing availability of large ALS clinical trial datasets have generated much interest in developing...