Intelligent Fuzzy System to Predict the Wisconsin Breast Cancer Dataset.

Decision Support Systems (DSSs) are solutions that serve decision-makers in their decision-making process. For the development of these intelligent systems, two primary components are needed: the knowledge database and the knowledge rule base. The objective of this research work was to implement and validate diverse clinical decision support systems supported by Mamdani-type fuzzy set theory using clustering and dynamic tables. The outcomes were evaluated with other works obtained from the literature to validate the suggested fuzzy systems for categorizing the Wisconsin breast cancer dataset. The fuzzy Inference Systems worked with different input features, according to the studies obtained from the literature. The outcomes confirm that most performance' metrics in several cases were greater than the achieved results from the literature for the output variable for the different Fuzzy Inference Systems-FIS, demonstrating superior precision.

Cryopreservation of the Microalgae Scenedesmus sp.

Each phytoplankton species presents a different behavior and tolerance to the cryopreservation process. Therefore, in a species-specific protocol, it is essential to ensure both growth and post-thawing cell viability. In this study, we explored the effect of cryopreservation of Scenedesmus sp. with two cryoprotectants, dimethyl sulfoxide (DMSO) and methanol (MET), at 5% and 10% inclusion for each. In the control treatment, the microalgae were not exposed to cryoprotective agents (Control). Three post-thawing cell viability criteria were used: no cell damage (NCD), cell damage (CD), and marked lesions (LM), and mitochondrial and cell membrane damage was evaluated by flow cytometry. The study was a 2 × 2 factorial design, with five replications by treatments, population growth, and cell damage evaluated from the fifth day after thawing. On the fifth day, the highest percentage of NCD was observed when the microalgae were cryopreserved with DMSO 5% (50%); Regarding the control group, it showed 0% NCD. Flow cytometry analysis reveals minor damage at the membrane and mitochondria (9-10.7%) when DMSO is used at both inclusion percentages (5-10%) after thawing. In the exponential phase, the highest growth rates, doubling time, and yield was observed in cryopreserved cells with MET 5%. The results suggest that DMSO 5% is an ideal treatment for cryopreserving microalgae Scenedesmus sp.

Framework for the Development of Data-Driven Mamdani-Type Fuzzy Clinical Decision Support Systems.

Clinical decision support systems (CDSS) have been designed, implemented, and validated to help clinicians and practitioners for decision-making about diagnosing some diseases. Within the CDSSs, we can find Fuzzy inference systems. For the reasons above, the objective of this study was to design, to implement, and to validate a methodology for developing data-driven Mamdani-type fuzzy clinical decision support systems using clusters and pivot tables. For validating the proposed methodology, we applied our algorithms on five public datasets including Wisconsin, Coimbra breast cancer, wart treatment (Immunotherapy and cryotherapy), and caesarian section, and compared them with other related works (Literature). The results show that the Kappa Statistics and accuracies were close to 1.0% and 100%, respectively for each output variable, which shows better accuracy than some literature results. The proposed framework could be considered as a deep learning technique because it is composed of various processing layers to learn representations of data with multiple levels of abstraction.