Author(s): Shamshiri MA; Krzyzak A; Kowal M; Korbicz J;

Microscopic analysis of breast cancer images is the primary task in diagnosing cancer malignancy. Recent attempts to automate this task have employed deep learning models whose success has depended on large volumes of data, while acquiring annotated data in biomedical domains is time-consuming and may not always be feasible. A typical strategy to address ...

Article GUID: 36758326

Author(s): Aktar M; Reyes J; Tampieri D; Rivaz H; Xiao Y; Kersten-Oertel M;

Purpose: Collateral evaluation is typically done using visual inspection of cerebral images and thus suffers from intra- and inter-rater variability. Large open databases of ischemic stroke patients are rare, limiting the use of deep learning methods in treatment decision-making.
Methods: We adapted a pre-trained Eff ...

Article GUID: 36635594

Author(s): Rjoub G; Wahab OA; Bentahar J; Cohen R; Bataineh AS;

In the context of distributed machine learning, the concept of federated learning (FL) has emerged as a solution to the privacy concerns that users have about sharing their own data with a third-party server. FL allows a group of users (often referred to as clients) to locally train a single machine learning model on their devices without sharing their ra ...

Article GUID: 35875592

Author(s): Al-Qudah R; Khamayseh Y; Aldwairi M; Khan S;

The need for a smart city is more pressing today due to the recent pandemic, lockouts, climate changes, population growth, and limitations on availability/access to natural resources. However, these challenges can be better faced with the utilization of new technologies. The zoning design of smart cities can mitigate these challenges. It identifies the ma ...

Article GUID: 35746171

Author(s): Rahman A, Zunair H, Reme TR, Rahman MS, Mahdy MRC

Malaria, one of the leading causes of death in underdeveloped countries, is primarily diagnosed using microscopy. Computer-aided diagnosis of malaria is a challenging task owing to the fine-grained variability in the appearance of some uninfected and infected class. In this paper, we transform a malaria parasite object detection dataset into a classificat ...

Article GUID: 33465520