A5102008313- Genetic factors in colorectal cancer
- Cancer Genomics and Diagnostics
- Multiple Myeloma Research and Treatments
- Smart Grid Energy Management
- Cell Adhesion Molecules Research
- Colorectal Cancer Treatments and Studies
- Health and Medical Research Impacts
- Gastric Cancer Management and Outcomes
- Lung Cancer Treatments and Mutations
- Microgrid Control and Optimization
- Monoclonal and Polyclonal Antibodies Research
- HER2/EGFR in Cancer Research
- Mathematical Biology Tumor Growth
- Vehicular Ad Hoc Networks (VANETs)
- Advanced MIMO Systems Optimization
- Explainable Artificial Intelligence (XAI)
- Heparin-Induced Thrombocytopenia and Thrombosis
- Smart Grid Security and Resilience
- IoT and Edge/Fog Computing
- Energy Harvesting in Wireless Networks
- Blockchain Technology Applications and Security
- Cooperative Communication and Network Coding
- Brain Tumor Detection and Classification
- Age of Information Optimization
- Advanced Neural Network Applications
Koç University
2021-2025
Rijnstate Hospital
2025
China University of Mining and Technology
2023-2024
National Institute of Pharmaceutical Education and Research
2024
Government of India
2024
Khyber Teaching Hospital
2022
COMSATS University Islamabad
2018
Pfizer (United States)
2016
The traditional supply chain system included smart objects to enhance intelligence, automation capabilities, and intelligent decision-making. Internet of Things (IoT) technologies are providing unprecedented opportunities efficiency reduce the cost existing chain. This article aims study prevailing explore benefits obtained after embedded networks IoT implanted. Short-range communication technologies, radio frequency identification (RFID), middleware, cloud computing extensively comprehended...
Automation in sample preparation improves accuracy, productivity, and precision bioanalysis. Moreover, it reduces resource consumption for repetitive procedures. Automated analysis allows uninterrupted handling of large volumes biological samples originating from preclinical clinical studies. significantly helps management complex testing methods where generation data is required process monitoring. Compared to traditional processes, automated procedures reduce associated expenses manual...
Purpose: Adverse reactions reported in patients treated with antibody-calicheamicin conjugates such as gemtuzumab ozogamicin (Mylotarg) and inotuzumab include thrombocytopenia sinusoidal obstruction syndrome (SOS). The objective of this experimental work was to investigate the mechanism for thrombocytopenia, characterize liver injury, identify potential safety biomarkers.Experimental Design: Cynomolgus monkeys were dosed intravenously at 6 mg/m2/dose once every 3 weeks a nonbinding conjugate...
Artificial intelligence (AI) is expected to be an integral part of radio resource management (RRM) in sixth-generation (6G) networks. However, the opaque nature complex deep learning (DL) models lacks explainability and robustness, posing a significant hindrance adoption practice. Furthermore, wireless communication experts stakeholders, concerned about potential vulnerabilities, such as data privacy issues or biased decision-making, express reluctance fully embrace these AI technologies. To...
The inherent complexity of biological matrices and presence several interfering substances in samples make them unsuitable for direct analysis. An effective sample preparation technique assists analyte enrichment, improving selectivity sensitivity bioanalytical method. Because key benefits employing 3D printed sorbent extraction, it has recently gained popularity across a variety industries. Applications printing the field research have grown recently, particularly areas miniaturization,...
Artificial intelligence (AI) is expected to significantly enhance radio resource management (RRM) in sixth-generation (6G) networks. However, the lack of explainability complex deep learning (DL) models poses a challenge for practical implementation. This paper proposes novel explainable AI (XAI)- based framework feature selection and model complexity reduction model-agnostic manner. Applied multi-agent reinforcement (MADRL) setting, our approach addresses joint sub-band assignment power...
Quantitative analysis of pre- and postprocedure CT images more reliably identified residual tumor local progression compared with visual assessment in patients who underwent microwave ablation colorectal liver metastases.
Integrated artificial intelligence (AI) and communication has been recognized as a key pillar of 6G beyond networks. In line with AI-native vision, explainability robustness in AI-driven systems are critical for establishing trust ensuring reliable performance diverse evolving environments. This paper addresses these challenges by developing robust explainable deep learning (DL)-based beam alignment engine (BAE) millimeter-wave (mmWave) multiple-input multiple-output (MIMO) systems. The...
In creating decision-making systems that work for autonomous cars regarding the weather, weather detection (WDS) play a salient role in adverse conditions. Deep learning techniques specify modalities of allowing vehicles to understand and appreciate what happens outside under different scenarios. This should provide adaptive concerning various dynamics environment, which is very pivotal systems. The framework as deep learning-based proposed this article improves accuracy recognizing...
Venetoclax and Azacitidine combination has recently been approved by the USFDA to treat old people with acute myeloid leukemia. Pharmaceutical formulations of these two drugs are expected be launched soon. Till date, an analytical method any type not reported in literature for quantification a single run. The current work set out establish HILIC-HPLC based assay simultaneous from mixed sample. developed employing Poroshell HILIC column. Ammonium formate (10 mM, pH 5.0) acetonitrile were used...
Background: Silver nanowires (Ag-NWs) are promising as a kind of novel conducting materials for the next generation nanodevice space application either in form interconnecting NWs to integrate nanodevices or transparent electrodes solar cell. In order explore possible Ag-NWs upper space, radiation hardness testing is important. Methods: this research work, total dose tolerance under proton environment investigated. were irradiated with ions MeV energy range. The varies from 5x1015 1x1017...
Nowadays, different schemes and ways are proposed to meet the user's load requirement of energy towards Demand Side (DS) in order encapsulate resources. However, this Load (LD) increases day by day. This increase LD is causing serious crises utility DS. As usage with demand respectively, peak increased these hours which affect customer's term high-cost prices. issue tackled using some their proper integration. Two-way communication done through Smart Grid (SG) between customers. Customers...
Ensuring ultra-reliable low-latency communication (URLLC) is crucial in the timely delivery of safety-critical messages vehicle-to-vehicle (V2V) communications. The stringent latency requirement URLLC requires usage finite block length information theory. Previously proposed resource allocation schemes for V2V rely on Shannon rate and do not incorporate spectrum into blocklength power optimization while relying solely slow-varying large-scale channel statistics. This paper investigates...
<title>Abstract</title> In pipelines and process equipment, especially in cold oceanic environments, gas hydrate development presents a serious problem to the petroleum industry. Getting around this efficiently requires an understanding of chemical thermodynamics formation. order forecast temperature formation, current investigation compares effectiveness three different types machine learning algorithms: Support Vector Regression (SVR), Artificial Neural Networks (ANNs), Decision Tree (DT)....
Future 6G-enabled vehicular networks face the challenge of ensuring ultra-reliable low-latency communication (URLLC) for delivering safety-critical information in a timely manner. Existing resource allocation schemes vehicle-to-everything (V2X) systems primarily rely on traditional optimization-based algorithms. However, these methods often fail to guarantee strict reliability and latency requirements URLLC applications dynamic environments due high complexity overhead solution...
Since the development of Smart Grid (SG), Home Energy Management (HEM) systems are emerged widely into it and consumers have an opportunity to schedule their smart appliances efficiently in homes. In this research, meta-heuristic techniques Harmony Search Algorithm (HSA), Pigeon Inspired Optimization (PIO) our proposed (HPIO) adopted home. The aim using above is reduce Electricity Cost (EC) Peak-to-Average Ratio (PAR). HEM further evaluate performance evaluated techniques. work, single home...
<p>Explainable and Robust Artificial Intelligence for Trustworthy Resource Management in 6G Networks. In this paper, we present an overview of the explainable robust AI techniques radio resource management. We explain how these methods can provide a systematic methodology interpreting decisions made by black-box models, improve robustness performance algorithms reducing model complexity convergence time. Besides, outlining core explainability techniques, also two practical case studies...
<p>Explainable and Robust Artificial Intelligence for Trustworthy Resource Management in 6G Networks. In this paper, we present an overview of the explainable robust AI techniques radio resource management. We explain how these methods can provide a systematic methodology interpreting decisions made by black-box models, improve robustness performance algorithms reducing model complexity convergence time. Besides, outlining core explainability techniques, also two practical case studies...