AIMC Topic: Reproducibility of Results

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Past and future uses of text mining in ecology and evolution.

Proceedings. Biological sciences
Ecology and evolutionary biology, like other scientific fields, are experiencing an exponential growth of academic manuscripts. As domain knowledge accumulates, scientists will need new computational approaches for identifying relevant literature to ...

Generalisation effects of predictive uncertainty estimation in deep learning for digital pathology.

Scientific reports
Deep learning (DL) has shown great potential in digital pathology applications. The robustness of a diagnostic DL-based solution is essential for safe clinical deployment. In this work we evaluate if adding uncertainty estimates for DL predictions in...

Explicit and automatic ejection fraction assessment on 2D cardiac ultrasound with a deep learning-based approach.

Computers in biology and medicine
BACKGROUND: Ejection fraction (EF) is a key parameter for assessing cardiovascular functions in cardiac ultrasound, but its manual assessment is time-consuming and subject to high inter and intra-observer variability. Deep learning-based methods have...

Delta Machine Learning to Improve Scoring-Ranking-Screening Performances of Protein-Ligand Scoring Functions.

Journal of chemical information and modeling
Protein-ligand scoring functions are widely used in structure-based drug design for fast evaluation of protein-ligand interactions, and it is of strong interest to develop scoring functions with machine-learning approaches. In this work, by expanding...

Expert surgeons and deep learning models can predict the outcome of surgical hemorrhage from 1 min of video.

Scientific reports
Major vascular injury resulting in uncontrolled bleeding is a catastrophic and often fatal complication of minimally invasive surgery. At the outset of these events, surgeons do not know how much blood will be lost or whether they will successfully c...

Leakage Prediction in Machine Learning Models When Using Data from Sports Wearable Sensors.

Computational intelligence and neuroscience
One of the major problems in machine learning is data leakage, which can be directly related to adversarial type attacks, raising serious concerns about the validity and reliability of artificial intelligence. Data leakage occurs when the independent...

Development of a deep learning-based auto-segmentation algorithm for hepatocellular carcinoma (HCC) and application to predict microvascular invasion of HCC using CT texture analysis: preliminary results.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Automatic segmentation has recently been developed to yield objective data. Prediction of microvascular invasion (MVI) of hepatocellular carcinoma (HCC) using radiomics has been reported.

Application of artificial intelligence in the diagnosis and prognostic prediction of ovarian cancer.

Computers in biology and medicine
In recent years, the wide application of artificial intelligence (AI) has dramatically improved the work efficiency of clinicians and reduced their workload. This review provides a glance at the latest advances in AI-assisted diagnosis and prognostic...

Carrying Position-Independent Ensemble Machine Learning Step-Counting Algorithm for Smartphones.

Sensors (Basel, Switzerland)
Current step-count estimation techniques use either an accelerometer or gyroscope sensors to calculate the number of steps. However, because of smartphones unfixed placement and direction, their accuracy is insufficient. It is necessary to consider t...