Prediction of the as Low as Diagnostically Acceptable CT Dose for Identification of the Inferior Alveolar Canal Using 3D Convolutional Neural Networks with Multi-Balancing Strategies.

Ionizing radiation is necessary for diagnostic imaging and deciding the right radiation dose is extremely critical to obtain a decent quality image. However, increasing the dosage to improve the image quality has risks due to the potential harm from ionizing radiation. Thus, finding the optimal as low as diagnostically acceptable (ALADA) dosage is an open research problem that has yet to be tackled using artificial intelligence (AI) methods.

Telepresence Robot System for People with Speech or Mobility Disabilities.

Due to an increase in the number of disabled people around the world, inclusive solutions are becoming a priority. People with disabilities may encounter many problems and may not be able to easily participate in various activities due to physical barriers, which may sometimes cause them to be frustrated and embarrassed. Recently, the emerging telepresence robot technology has been proposed to enable people with disabilities to increase their presence by incorporating information and communications technology (ICT) into robotics platforms.

Semantic textual similarity for modern standard and dialectal Arabic using transfer learning.

Semantic Textual Similarity (STS) is the task of identifying the semantic correlation between two sentences of the same or different languages. STS is an important task in natural language processing because it has many applications in different domains such as information retrieval, machine translation, plagiarism detection, document categorization, semantic search, and conversational systems. The availability of STS training and evaluation data resources for some languages such as English has led to good performance systems that achieve above 80% correlation with human judgment.