Intelligent Sign Multi-Language Real-Time Prediction System with Effective Data Preprocessing

A multidisciplinary approach for developing an intelligent sign multi-language recognition system to greatly enhance deaf-mute communication will be discussed and implemented. This involves designing a low-cost glove-based sensing system, collecting large and diverse datasets, preprocessing the data, and using efficient machine learning models. Furthermore, the glove is integrated with a user-friendly mobile application called “Life-sign” for this system. The main goal of this work is to minimize the processing time of machine learning classifiers while maintaining higher accuracy performance. This is achieved by using effective preprocessing algorithms to handle noisy and inconsistent data. Testing and iterating approaches have been applied to various classifiers to refine and improve their accuracy in the recognition process. Additionally, the Extra Trees (ET) classifier has been identified as the best algorithm, with results proving successful gesture prediction at an average accuracy of about 99.54%. A smart optimization feature has been implemented to control the size of data transferred via Bluetooth, allowing for fast recognition of consecutive gestures. Real-time performance has been measured through extensive experimental testing on various consecutive gestures, specifically referring to Arabic Sign Language (ArSL). The results have demonstrated that the system guarantees consecutive gesture recognition with a lower delay of 50 milliseconds.

Burden of venous thromboembolism in patients with pancreatic cancer

Pancreatic cancer(PC)is a devastating malignancy with fewer than 10%of patients being alive at 5 years after diagnosis.Venous thromboembolism(VTE)occurs in approximatively 20%of patients with PC,resulting in increased morbidity,mortality and significant health care costs.The management of VTE is particularly challenging in these frail patients.Adequate selection of the most appropriate anticoagulant for each individual patient according to the current international guidelines is warranted for overcoming treatment challenges.The International Initiative on Thrombosis and Cancer multi-language web-based mobile application(downloadable for free at www.itaccme.com)has been developed to help clinicians in decision making in the most complex situations.In this narrative review,we will discuss the contemporary epidemiology and burden of VTE in PC patients,the performances and limitations of current risk assessment models to predict the risk of VTE,as well as evidence from recent clinical trials for the primary prophylaxis and treatment of cancer-associated VTE that support updated clinical practice guidelines.