PermQRDroid: Android malware detection with novel attention layered mini-ResNet architecture over effective permission information image.

Background: The Android operating system holds the vast majority of the market share in smart device usage worldwide. The Android operating system, which is of interest to users, is increasing its usage rate day by day due to its open source nature and free applications. Applications can be installed on the Android operating system from official application markets and unofficial third-party environments, which poses a great risk to users' privacy and security.

Prediction of pathological complete response to neoadjuvant chemotherapy in locally advanced breast cancer by using a deep learning model with 18F-FDG PET/CT.

Objectives: The aim of the study is 18F-FDG PET/CT imaging by using deep learning method are predictive for pathological complete response pCR after Neoadjuvant chemotherapy (NAC) in locally advanced breast cancer (LABC).

Introduction: NAC is the standard treatment for locally advanced breast cancer (LABC). Pathological complete response (pCR) after NAC is considered a good predictor of disease-free survival (DFS) and overall survival (OS).

Android malware detection using hybrid ANFIS architecture with low computational cost convolutional layers.

Background: Android is the most widely used operating system all over the world. Due to its open nature, the Android operating system has become the target of malicious coders. Ensuring privacy and security is of great importance to Android users.