AIMC Topic: Confidence Intervals

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Confidence interval forecasting model of small watershed flood based on compound recurrent neural networks and Bayesian.

PloS one Apr 21, 2025
Flood forecasting exhibits rapid fluctuations, water level forecasting shows great uncertainty and inaccuracy in small watersheds, and the reliability and accuracy performance of traditional probability forecasting is often unbalanced. This study com...
China Bayes Theorem Confidence Intervals Floods Recurrent Neural Networks Neural Networks, Computer Forecasting
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Development and validation of MRI-based deep learning models for prediction of microsatellite instability in rectal cancer.

Cancer medicine May 8, 2021
BACKGROUND: Microsatellite instability (MSI) predetermines responses to adjuvant 5-fluorouracil and immunotherapy in rectal cancer and serves as a prognostic biomarker for clinical outcomes. Our objective was to develop and validate a deep learning m...
Humans Adenocarcinoma Retrospective Studies Magnetic Resonance Imaging Aged Female Rectal Neoplasms Area Under Curve Aged, 80 and over Confidence Intervals Microsatellite Instability Young Adult Adult Male Middle Aged Deep Learning Logistic Models
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Relation of Quantitative Histologic and Radiologic Breast Tissue Composition Metrics With Invasive Breast Cancer Risk.

JNCI cancer spectrum Feb 6, 2021
BACKGROUND: Benign breast disease (BBD) is a strong breast cancer risk factor, but identifying patients that might develop invasive breast cancer remains a challenge.
Humans Female Adult Breast Neoplasms Middle Aged Case-Control Studies Diagnosis, Computer-Assisted Risk Factors Aged Aged, 80 and over Young Adult Breast Diseases Supervised Machine Learning Confidence Intervals Odds Ratio Breast Density Age Factors Mammography Biopsy Breast
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C-Norm: a neural approach to few-shot entity normalization.

BMC bioinformatics Dec 29, 2020
BACKGROUND: Entity normalization is an important information extraction task which has gained renewed attention in the last decade, particularly in the biomedical and life science domains. In these domains, and more generally in all specialized domai...
Databases as Topic Knowledge Phenotype Ecosystem Bacteria Confidence Intervals Humans Neural Networks, Computer Machine Learning Algorithms
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Using Auto-Segmentation to Reduce Contouring and Dose Inconsistency in Clinical Trials: The Simulated Impact on RTOG 0617.

International journal of radiation oncology, biology, physics Nov 13, 2020
PURPOSE: Contouring inconsistencies are known but understudied in clinical radiation therapy trials. We applied auto-contouring to the Radiation Therapy Oncology Group (RTOG) 0617 dose escalation trial data. We hypothesized that the trial heart doses...
Proportional Hazards Models Radiotherapy Dosage Clinical Trials, Phase III as Topic Statistics, Nonparametric Humans Heart Algorithms Middle Aged Organs at Risk Tomography, X-Ray Computed Deep Learning Confidence Intervals Aged, 80 and over Lung Neoplasms Linear Models Adult Carcinoma, Non-Small-Cell Lung Female Male Aged
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Electromechanical-assisted training for walking after stroke.

The Cochrane database of systematic reviews Oct 22, 2020
BACKGROUND: Electromechanical- and robot-assisted gait-training devices are used in rehabilitation and might help to improve walking after stroke. This is an update of a Cochrane Review first published in 2007 and previously updated in 2017.
Confidence Intervals Odds Ratio Walking Speed Orthotic Devices Electric Stimulation Therapy Stroke Rehabilitation Walking Gait Combined Modality Therapy Exercise Therapy Robotics Bias Equipment Design Cause of Death Humans Aged Middle Aged Randomized Controlled Trials as Topic
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Issues associated with deploying CNN transfer learning to detect COVID-19 from chest X-rays.

Physical and engineering sciences in medicine Oct 6, 2020
Covid-19 first occurred in Wuhan, China in December 2019. Subsequently, the virus spread throughout the world and as of June 2020 the total number of confirmed cases are above 4.7 million with over 315,000 deaths. Machine learning algorithms built on...
Humans Neural Networks, Computer X-Rays Artifacts COVID-19 Confidence Intervals SARS-CoV-2 Databases as Topic Deep Learning Thorax Image Processing, Computer-Assisted
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Active Learning of Bayesian Linear Models with High-Dimensional Binary Features by Parameter Confidence-Region Estimation.

Neural computation Aug 14, 2020
In this letter, we study an active learning problem for maximizing an unknown linear function with high-dimensional binary features. This problem is notoriously complex but arises in many important contexts. When the sampling budget, that is, the num...
Linear Models Humans Bayes Theorem Supervised Machine Learning Confidence Intervals
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A network model of affective odor perception.

PloS one Jul 30, 2020
The affective appraisal of odors is known to depend on their intensity (I), familiarity (F), detection threshold (T), and on the baseline affective state of the observer. However, the exact nature of these relations is still largely unknown. We there...
Male Humans Olfactory Perception Neural Networks, Computer Arousal Models, Biological Female Physical Stimulation Odorants Young Adult Confidence Intervals
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Screening of Parkinsonian subtle fine-motor impairment from touchscreen typing via deep learning.

Scientific reports Jul 28, 2020
Fine-motor impairment (FMI) is progressively expressed in early Parkinson's Disease (PD) patients and is now known to be evident in the immediate prodromal stage of the condition. The clinical techniques for detecting FMI may not be robust enough and...
Parkinson Disease Humans Self Report Female Confidence Intervals Cohort Studies Male Motor Activity ROC Curve Middle Aged Smartphone Deep Learning Mass Screening
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