Cardiovascular disease is a substantial cause of mortality and morbidity in the world. In clinical data analytics, it great challenge to predict heart survivor. Data mining transforms huge amounts raw generated by health industry into useful information that can help making informed decisions. Various studies proved significant features play key role improving performance machine learning models. This study analyzes failure survivors from dataset 299 patients admitted hospital. The aim find...

Abstract Efficient word representation techniques (word embeddings) with modern machine learning models have shown reasonable improvement on automatic text classification tasks. However, the effectiveness of such has not been evaluated yet in terms insufficient vector for training. Convolutional Neural Network achieved significant results pattern recognition, image analysis, and classification. This study investigates application CNN model problems by experimentation analysis. We trained our...

Face recognition has made significant advances in the last decade, but robust commercial applications are still lacking. Current authentication/identification limited to controlled settings, e.g., pose and illumination changes, with user usually aware of being screened collaborating process. Among others, changes limited. To address challenges from looser restrictions, this paper proposes a novel framework for real-world face uncontrolled settings named Analysis Commercial Entities (FACE)....

Face recognition provides many advantages compared with other available biometrics, but it is particularly subject to spoofing. The most accurate methods in literature addressing this problem, rely on the estimation of three-dimensionality faces, which heavily increase whole cost system. This paper proposes an effective and efficient solution problem face Starting from a set automatically located facial points, we exploit geometric invariants for detecting replay attacks. presented results...

The proliferation of user-generated content on social media has made opinion mining an arduous job. As a microblogging platform, Twitter is being used to collect views about products, trends, and politics. Sentiment analysis technique analyze the attitude, emotions opinions different people towards anything, it can be carried out tweets public news, policies, movements, personalities. By employing Machine Learning models, performed without reading manually. Their results could assist...

It is widely known that a quick disclosure of the COVID-19 can help to reduce its spread dramatically. Transcriptase polymerase chain reaction could be more useful, rapid, and trustworthy technique for evaluation classification disease. Currently, computerized method classifying computed tomography (CT) images chests crucial speeding up detection while epidemic rapidly spreading. In this article, authors have proposed an optimized convolutional neural network model (ADECO-CNN) divide...

The prediction of heart failure survivors is a challenging task and helps medical professionals to make the right decisions about patients. Expertise experience are required care for Machine Learning models can help with understanding symptoms cardiac disease. However, manual feature engineering requires expertise select appropriate technique. This study proposes smart healthcare framework using Internet-of-Things (IoT) cloud technologies that improve patients' survival without considering...

Deep learning methods have achieved great success in medical image analysis domain. However, most of them suffer from slow convergency and high computing cost, which prevents their further widely usage practical scenarios. Moreover, it has been proved that exploring embedding context knowledge deep network can significantly improve accuracy. To emphasize these tips, we present CDT-CAD, i.e., context-aware deformable transformers for end-to-end chest abnormality detection on X-Ray images....

Unmanned aerial vehicles (UAVs) are promising remote sensors capable of reforming sensing applications. However, for artificial intelligence (AI)-guided tasks, like land cover mapping and ground-object mapping, most deep learning-based architectures fail to extract scale-invariant features, resulting in poor performance accuracy. In this context, the article proposes a superpixel-aided multiscale convolutional neural network (CNN) architecture avoid misclassification complex urban images.The...

Edge computing can potentially play a crucial role in enabling user authentication and monitoring through context-aware biometrics military/battlefield applications. For example, Internet of Military Things (IoMT) or Battlefield (IoBT),an increasing number ubiquitous sensing devices worn by military personnel embedded within equipment (combat suit, instrumented helmets, weapon systems, etc.) are capable acquiring variety static dynamic (e.g., face, iris, periocular, fingerprints, heart-rate,...

Ascertaining the impact of research is significant for community and academia all disciplines. The only prevalent measure associated with quantification quality citation-count. Although a number citations play role in academic research, sometimes can be biased or made to discuss weaknesses shortcomings research. By considering sentiment recognizing patterns text aid understanding opinion peer will also help quantifying articles. Efficient feature representation combined machine learning...

Colonic adenocarcinoma is a disease severely endangering human life caused by mucosal epidermal carcinogenesis. The segmentation of potentially cancerous glands the key in detection and diagnosis colonic adenocarcinoma. appearance tissue different gland colon pathological images, it impossible to accurately segment changes from benign malignant using single network. Given these issues, two-path algorithm image based on local semantic guidance proposed this paper. improved candidate region...