BACKGROUND: Despite the recent advances in cancer treatment, the therapeutic options for patients with biliary tract cancer are still very limited and the prognosis very poor. More than 50% of newly diagnosed patients with biliary tract cancer are not amenable to curative surgical treatment and thus treated with palliative systemic treatment. Malignant bile duct obstructions… →
The number of modern applications containing both the backend and frontend code with one or more generative AI models is increasing rapidly. Developers are required to keep up with the expanding field of AI engineering in order to incorporate these models into their latest projects. Currently, the major issue that developers are facing is limited… →
Visual understanding is the abstracting of high-dimensional visual signals like images and videos. Many problems are involved in this process, ranging from depth prediction and vision-language correspondence to classification and object grounding, which include tasks defined along spatial and temporal axes and tasks defined along coarse to fine granularity, like object grounding. In light of… →
Speech recognition is a rapidly evolving field that enables machines to understand and transcribe human speech across various languages. This technology is vital for virtual assistants, automated transcription services, and language translation applications. Despite significant advancements, the challenge of covering all languages, particularly low-resource ones, remains substantial. A major issue in speech recognition is the… →
This study was aimed to evaluate the impact of community pharmacy (CP)-based medication therapy management (MTM) program on clinical and humanistic outcomes in patients with uncontrolled diabetes. An open label, parallel-group randomised controlled trial was undertaken at a community pharmacy in Riyadh city, Kingdom of Saudi Arabia. Patients with a diagnosis of uncontrolled diabetes (HbA1c… →
The Role of AI in Medicine: AI simulates human intelligence in machines and has significant applications in medicine. AI processes large datasets to identify patterns and build adaptive models, particularly in deep learning for medical image analysis, such as X-rays and MRIs. Multi-agent systems enhance distributed AI, enabling medical robots to assist in surgeries and… →
Efficiently integrating AI agents with various applications and tools can be challenging. Traditionally, developers have approached such tasks using individual APIs or creating custom solutions for each integration. These methods, however, come with significant drawbacks. They often lack consistency, require extensive coding and maintenance, and can lead to errors in tool calls and data handling.… →
Software vulnerability detection has seen substantial advancements in integrating deep learning models, which have shown high accuracy in identifying potential vulnerabilities within software. These models analyze code to detect patterns and anomalies that indicate weaknesses. However, despite their effectiveness, these models are not immune to attacks. Specifically, adversarial attacks, which involve manipulating input data to… →
Large Language Models (LLMs) have revolutionized natural language processing, demonstrating exceptional performance across various tasks. The Scaling Law suggests that as model size increases, LLMs develop emergent abilities, enhancing their context understanding and long sequence handling capabilities. This growth enables LLMs to generate coherent responses and power applications like document summarization, code generation, and conversational… →
The prospects and scope for automation in digital lives are expanding with the advances in instruction following, coding, and tool-use abilities of large language models (LLMs). Most day-to-day digital tasks involve complex activities across various applications, with reasoning and decision-making based on intermediate results. However, the responsive development of such autonomous agents needs rigorous, reproducible,… →