The development of an efficient artificial intelligence-based classification approach for colorectal cancer response to radiochemotherapy: deep learning vs. machine learning.

Colorectal cancer (CRC) is a form of cancer that impacts both the rectum and colon. Typically, it begins with a small abnormal growth known as a polyp, which can either be non-cancerous or cancerous. Therefore, early detection of colorectal cancer as the second deadliest cancer after lung cancer, can be highly beneficial.

Optimization of Bioactive Compound Extraction from Iranian Brown Macroalgae with Ultrasound and Microwave Methods Using Fuzzy Logic.

In this study, three extraction methods of bioactive compounds from the brown algae were ranked using the fuzzy weighting system in two stages, ranking between different conditions and choosing the optimal conditions for each extraction method separately. The inputs included extraction yield (EY), antioxidant activity (DPPH), total flavonoid content (TFC), total phenolic content (TPC), total phlorotannin content (TPhC), time, temperature, power, and cost. The top ranks of the first phase output included: Maceration Extraction (ME) with a score of 52.

PointCloud-At: Point Cloud Convolutional Neural Networks with Attention for 3D Data Processing.

The rapid growth in technologies for 3D sensors has made point cloud data increasingly available in different applications such as autonomous driving, robotics, and virtual and augmented reality. This raises a growing need for deep learning methods to process the data. Point clouds are difficult to be used directly as inputs in several deep learning techniques.