In the paper Improved Overlap-Based Undersampling for Imbalanced Dataset Classification with Application to Epilepsy and Parkinson’s Disease, the authors introduced two new methods that address the class overlap problem in imbalanced datasets. The methods involve identification and removal of potentially overlapped majority class instances. Extensive evaluations were carried out using 136 datasets and compared against several state-of-the-art methods. Results showed competitive performance with those methods, and statistical tests proved significant improvement in classification results. The discussion on the paper related to the behavioral analysis of class overlap and method validation was raised by Fernández. In this article, the response to the discussion is delivered. Detailed clarification and supporting evidence to answer all the points raised are provided.
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Extensive development has taken place in the field of image fusion and various algorithms of image fusion have attracted the attention of many researchers in the recent past. Various algorithms of image fusion are used to combine information from multiple source images into a single fused image. In this paper, fusion of multiple images using fuzzy transform is proposed. Images to be fused are initially decomposed into same size blocks. These blocks are then fuzzy transformed and fused using maxima coefficient value-based fusion rule. Finally, the fused image is obtained by performing inverse fuzzy transform. The performance of the proposed algorithm is evaluated by performing experiments on multifocus, medical and visible/infrared images. Further, the performance of the proposed algorithm is compared with the state-of-the-art image fusion algorithms, both subjectively and objectively. Experimental results and comparative study show that the proposed fusion algorithm fuses the multiple images effectively and produces better fusion results for medical and visible/infrared images.
Digital imaging and medical reporting have acquired an essential role in healthcare, but the main challenge is the storage of a high volume of patient data. Although newer technologies are already introduced in the medical sciences to save records size, Big Data provides advancements by storing a large amount of data to improve the efficiency and quality of patient treatment with better care. It provides intelligent automation capabilities to reduce errors than manual inputs. Large numbers of research papers on big data in the medical field are studied and analyzed for their impacts, benefits, and applications. Big data has great potential to support the digitalization of all medical and clinical records and then save the entire data regarding the medical history of an individual or a group. This paper discusses big data usage for various industries and sectors. Finally, 12 significant applications for the medical field by the implementation of big data are identified and studied with a brief description. This technology can be gainfully used to extract useful information from the available data by analyzing and managing them through a combination of hardware and software. With technological advancement, big data provides health-related information for millions of patient-related to life issues such as lab tests reporting, clinical narratives, demographics, prescription, medical diagnosis, and related documentation. Thus, Big Data is essential in developing a better yet efficient analysis and storage healthcare services. The demand for big data applications is increasing due to its capability of handling and analyzing massive data. Not only in the future but even now, Big Data is proving itself as an axiom of storing, developing, analyzing, and providing overall health information to the physicians.
The COVID-19 outbreak has resulted in the manufacturing and service sectors being badly hit globally. Since there are no vaccines or any proven medical treatment available, there is an urgent need to take necessary steps to prevent the spread of this virus. As the virus spreads with human-to-human interaction, lockdown has been declared in many countries, and the public is advised to observe social distancing strictly. Robots can undertake human-like activities and can be gainfully programmed to replace some of the human interactions. Through this paper, we identify and propose the introduction of robots to take up this challenge in the fight against the COVID-19 pandemic. We did a comprehensive review of the literature to identify robots’ possible applications in the management of epidemics and pandemics of this nature. We have reviewed the available literature through the search engines of PubMed, SCOPUS, Google Scholar, and Research Gate. A comprehensive review of the literature identified different types of robots being used in the medical field. We could find several vital applications of robots in the management of the COVID-19 pandemic. No doubt technology comes with a cost. In this paper, we identified how different types of robots are used gainfully to deliver medicine, food, and other essential items to COVID-19 patients who are under quarantine. Therefore, there is extensive scope for customising robots to undertake hazardous and repetitive jobs with precision and reliability.
Virtual reality (VR) has applications in cardiology to create enhancement, thereby improving the quality of associated planning, treatment and surgery. The need is to study different applications of this technology in the field of cardiology. We have studied research papers on VR and its applications in cardiology through a detailed bibliometric analysis. The study identified five significant steps for proper implementation of this technology in cardiology. Some challenges are to be undertaken by using this technology, and they can provide some benefits; thus, authors contemplate extensive research and development. This study also identifies 10 major VR technology applications in cardiology and provided a brief description. This innovative technology helps a heart surgeon to perform complex heart surgery effectively. Thus, VR applications have the potential for improving decision-making, which helps save human life. VR plays a significant role in the development of a surgical procedure. This technology undertakes 3D heart model information in full colour, which helps to analyze the overall heart vane, blockage and blood flow. With the help of this digital technology, a surgeon can improve the accuracy of heart surgery, and he can simulate the surgery. A surgeon can undertake surgery in a virtual environment on a virtual patient. The unique purpose of this technology is to practice pre-operatively on the specific circumstance. A cardiologist can also check the proper status of inner and outer heart wall layer. Thus, by using this 3D information, the surgeon can now interact with heart data/information without any physical touch. This technology opens a new opportunity to improve the heart surgery and development in cardiovascular treatment to improve patient outcome.
Background: Ovarian endometriomas have been shown to have a negative effect on fertility. There is a dilemma on the timing for surgery either before or after the fertility treatment. By delaying surgical treatment for infertile patients with endometriomas, medical treatment has become an important choice for these patients. The objectives of this review were to compare the efficacy of medical treatment on endometrioma size and endometriosis-associated pelvic pain (EAPP).
Methods: We performed a systematic review and meta-analysis examining women who have endometrioma and underwent medical therapy for endometrioma size reduction. The primary outcome measure was endometrioma size reduction. Secondary outcome measures EAPP.
Results: We included 14 studies for the meta-analysis. We performed a systematic review and meta-analysis examining women with endometrioma who underwent medical therapy for endometrioma size reduction. The primary outcome measure was endometrioma size reduction. Secondary outcome measure is EAPP. The majority of the studies were non-randomized controlled trials (RCTs; 9/14), and five were RCTs. Women who received medical treatment have a significant endometrioma size reduction in diameter compared to women not receiving any medical treatment or placebo (MD −9.66mm; 95% CI [−13.85, −5.46], three studies, 467 women, I2=96%) and a reduction in visual analog scale (VAS) for EAPP (MD −2.64; 95% CI [−3.31, −1.97], two studies, 338 women, I2=0%). Women who received dienogest (DNG) treatment have a significant endometrioma size reduction in diameter (MD −4.61mm; 95% CI [−9.08, −0.15], three studies, 220 women, I2=96%). Compared to women receiving other medical treatments, women receiving DNG treatment had more VAS reduction of EAPP (MD −0.46; 95% CI [−0.62, −0.31], four studies, 451 women, I2=85%).
Conclusions: The use of medical therapy is associated with endometrioma size reduction and a reduction in endometriosis-related pain when compared with no medical treatment given. With the availability of various medical options, surgery can thus be avoided to minimize the risk of damage to the ovarian reserves.
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