AIMC Topic: Machine Learning

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Polygenic modelling and machine learning approaches in pharmacogenomics: Importance in downstream analysis of genome-wide association study data.

British journal of clinical pharmacology
Genome-wide association studies (GWAS) have identified genetic variations associated with adverse drug effects in pharmacogenomics (PGx) research. However, interpreting the biological implications of these associations remains a challenge. This revie...

The impact of misclassification errors on the performance of biomarkers based on next-generation sequencing, a simulation study.

Journal of biopharmaceutical statistics
The development of next-generation sequencing (NGS) opens opportunities for new applications such as liquid biopsy, in which tumor mutation genotypes can be determined by sequencing circulating tumor DNA after blood draws. However, with highly dilute...

AI Model Versus Clinician Otoscopy in the Operative Setting for Otitis Media Diagnosis.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
Prior work has demonstrated improved accuracy in otitis media diagnosis based on otoscopy using artificial intelligence (AI)-based approaches compared to clinician evaluation. However, this difference in accuracy has not been shown in a setting resem...

A Comparative Analysis of Data Synthesis Techniques to Improve Classification Accuracy of Raman Spectroscopy Data.

Journal of chemical information and modeling
Raman spectra are examples of high dimensional data that can often be limited in the number of samples. This is a primary concern when Deep Learning frameworks are developed for tasks such as chemical species identification, quantification, and diagn...

Identifying primary tumor site of origin for liver metastases via a combination of handcrafted and deep learning features.

The journal of pathology. Clinical research
Liver is one of the most common sites for metastases, which can occur on account of primary tumors from multiple sites of origin. Identifying the primary site of origin (PSO) of a metastasis can help in guiding therapeutic options for liver metastase...

Machine learning-based model construction and identification of dominant factor for simultaneous sulfide and nitrate removal process.

Bioresource technology
Accurate water quality prediction models are essential for the successful implementation of the simultaneous sulfide and nitrate removal process (SSNR). Traditional models, such as regression and analysis of variance, do not provide accurate predicti...

Machine learning methods for tracer kinetic modelling.

Nuklearmedizin. Nuclear medicine
Tracer kinetic modelling based on dynamic PET is an important field of Nuclear Medicine for quantitative functional imaging. Yet, its implementation in clinical routine has been constrained by its complexity and computational costs. Machine learning ...

Residential water and energy consumption prediction at hourly resolution based on a hybrid machine learning approach.

Water research
Predicting water and energy consumption at high resolution over a short-term horizon is critical for water and energy resource management. Water and energy are shown to be closely interlinked in household consumption. However, hourly predictions are ...

An interpretable ensemble learning model facilitates early risk stratification of ischemic stroke in intensive care unit: Development and external validation of ICU-ISPM.

Computers in biology and medicine
Ischemic stroke (IS) is a common and severe condition that requires intensive care unit (ICU) admission, with high mortality and variable prognosis. Accurate and reliable predictive tools that enable early risk stratification can facilitate intervent...

A Machine-Learning-Based Approach to Prediction of Biogeographic Ancestry within Europe.

International journal of molecular sciences
Data obtained with the use of massive parallel sequencing (MPS) can be valuable in population genetics studies. In particular, such data harbor the potential for distinguishing samples from different populations, especially from those coming from adj...