AIMC Topic: Reproducibility of Results

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Development of a highly sensitive and specific ELISA method for the determination of l-corydalmine in SD rats with monoclonal antibody.

Journal of chromatography. B, Analytical technologies in the biomedical and life sciences
l-Corydalmine (l-CDL) is a potent analgesic constituent of the traditional Chinese medicine, Rhizoma Corydalis. However, the pharmacokinetic process and tissue distribution of l-CDL in vivo are still unknown. Therefore, it is necessary to establish a...

A novel and reliable computational intelligence system for breast cancer detection.

Medical & biological engineering & computing
Cancer is the second important morbidity and mortality factor among women and the most incident type is breast cancer. This paper suggests a hybrid computational intelligence model based on unsupervised and supervised learning techniques, i.e., self-...

A Computational-Based Method for Predicting Drug-Target Interactions by Using Stacked Autoencoder Deep Neural Network.

Journal of computational biology : a journal of computational molecular cell biology
Identifying the interaction between drugs and target proteins is an important area of drug research, which provides a broad prospect for low-risk and faster drug development. However, due to the limitations of traditional experiments when revealing d...

Depression recognition according to heart rate variability using Bayesian Networks.

Journal of psychiatric research
BACKGROUND: Doctors mainly use scale tests and subjective judgment in the clinical diagnosis of depression. Researches have demonstrated that depression is associated with the dysfunction of the autonomic nervous system (ANS), where its modulation ca...

A machine learning approach for the identification of new biomarkers for knee osteoarthritis development in overweight and obese women.

Osteoarthritis and cartilage
OBJECTIVE: Knee osteoarthritis (OA) is among the higher contributors to global disability. Despite its high prevalence, currently, there is no cure for this disease. Furthermore, the available diagnostic approaches have large precision errors and low...

Comparative approaches for classification of diabetes mellitus data: Machine learning paradigm.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Diabetes is a silent killer. The main cause of this disease is the presence of excessive amounts of metabolites such as glucose. There were about 387 million diabetic people all over the world in 2014. The financial burden o...

Computer-assisted cytologic diagnosis in pancreatic FNA: An application of neural networks to image analysis.

Cancer cytopathology
BACKGROUND: Fine-needle aspiration (FNA) biopsy is an accurate method for the diagnosis of solid pancreatic masses. However, a significant number of cases still pose a diagnostic challenge. The authors have attempted to design a computer model to aid...

[Evaluation of equations using cystatin C for estimation of the glomerular filtration rate in healthy adult population of canidates for kidney donors.].

Revista de la Facultad de Ciencias Medicas (Cordoba, Argentina)
The determination of the glomerular filtration rate (GFR) is critical for the selection of potential kidney donors. Methods of measurement of GFR are impractical and complex, which led to development of equations to estimate GFR. Objective: To evalua...

A Novel Energy-Efficient Approach for Human Activity Recognition.

Sensors (Basel, Switzerland)
In this paper, we propose a novel energy-efficient approach for mobile activity recognition system (ARS) to detect human activities. The proposed energy-efficient ARS, using low sampling rates, can achieve high recognition accuracy and low energy con...

Optimisation of a machine learning algorithm in human locomotion using principal component and discriminant function analyses.

PloS one
Assessment methods in human locomotion often involve the description of normalised graphical profiles and/or the extraction of discrete variables. Whilst useful, these approaches may not represent the full complexity of gait data. Multivariate statis...