AIMC Topic: Regression Analysis

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Identification of optimal prediction models using multi-omic data for selecting hybrid rice.

Heredity
Genomic prediction benefits hybrid rice breeding by increasing selection intensity and accelerating breeding cycles. With the rapid advancement of technology, other omic data, such as metabolomic data and transcriptomic data, are readily available fo...

Comparison of long-term outcomes of laparoscopic and robot-assisted laparoscopic partial nephrectomy.

The Kaohsiung journal of medical sciences
In this study, we compared the long-term oncological and functional outcomes of laparoscopic partial nephrectomy (LPN) and robot-assisted laparoscopic partial nephrectomy (RAPN) performed in the treatment of renal tumors. The data of 142 patients (RA...

Financial time series forecasting using twin support vector regression.

PloS one
Financial time series forecasting is a crucial measure for improving and making more robust financial decisions throughout the world. Noisy data and non-stationarity information are the two key factors in financial time series prediction. This paper ...

Regression convolutional neural network for improved simultaneous EMG control.

Journal of neural engineering
OBJECTIVE: Deep learning models can learn representations of data that extract useful information in order to perform prediction without feature engineering. In this paper, an electromyography (EMG) control scheme with a regression convolutional neur...

Predicting forced vital capacity (FVC) using support vector regression (SVR).

Physiological measurement
OBJECTIVE: Spirometry, as the gold standard approach in the diagnosis of chronic obstructive pulmonary disease (COPD), has strict end of test (EOT) criteria (e.g. complete exhalation), which cannot be met by patients with compromised health states. T...

Towards end-to-end likelihood-free inference with convolutional neural networks.

The British journal of mathematical and statistical psychology
Complex simulator-based models with non-standard sampling distributions require sophisticated design choices for reliable approximate parameter inference. We introduce a fast, end-to-end approach for approximate Bayesian computation (ABC) based on fu...

Software Development Effort Estimation Using Regression Fuzzy Models.

Computational intelligence and neuroscience
Software effort estimation plays a critical role in project management. Erroneous results may lead to overestimating or underestimating effort, which can have catastrophic consequences on project resources. Machine-learning techniques are increasingl...

An automated data verification approach for improving data quality in a clinical registry.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The quality of data is crucial for clinical registry studies as it impacts credibility. In the regular practice of most such studies, a vulnerability arises from researchers recording data on paper-based case report forms (C...

Prediction of mortality following pediatric heart transplant using machine learning algorithms.

Pediatric transplantation
BACKGROUND: Optimizing transplant candidates' priority for donor organs depends on the accurate assessment of post-transplant outcomes. Due to the complexity of transplantation and the wide range of possible serious complications, recipient outcomes ...

Computational prediction of diagnosis and feature selection on mesothelioma patient health records.

PloS one
BACKGROUND: Mesothelioma is a lung cancer that kills thousands of people worldwide annually, especially those with exposure to asbestos. Diagnosis of mesothelioma in patients often requires time-consuming imaging techniques and biopsies. Machine lear...