HeteroSAS: A Heterogeneous Resource Management Framework for "All-in-the-Air" Social Airborne Sensing in Disaster Response

Rashid, Tahmid; Zhang, Daniel Yue; Wang, Dong

doi:10.1109/dcoss52077.2021.00034

Cited by 5 publications

(4 citation statements)

References 31 publications

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“…Surgeons may make more informed decisions, receive real-time feedback, and complete complex surgeries more quickly thanks to AI-powered robotic equipment. By examining a sizable amount of patient data, medical literature, and clinical recommendations, AI enables data-driven decision making [58]. AI systems can extract pertinent insights, spot patterns, and help healthcare practitioners make decisions that are precise and supported by the available data.…”

Section: A Glimpse Into the Future: Ai's Impact On Healthcare Deliverymentioning

confidence: 99%

The Future of Medicine: Harnessing the Power of AI for Revolutionizing Healthcare

Harry¹

2023

ijmdsa

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Artificial intelligence (AI) has the potential to completely change how healthcare is delivered, revolutionizing the healthcare sector. Precision diagnosis, proactive disease prevention, personalised treatment plans, real-time monitoring and intervention, improved medical imaging, streamlined healthcare workflows, ethical considerations, and the potential future implications of AI in healthcare are all explored in this paper. The first section describes how precision diagnosis using AI technologies is improving diagnostic accuracy. Personalised treatment regimens and earlier disease detection are made possible by machine learning algorithms' analysis of enormous volumes of patient data. Additionally, AI makes it possible to actively prevent disease by using predictive analytics to identify those who are most likely to develop a particular condition, enabling early intervention and tailored preventive actions. The second segment focuses on how AI is transforming therapeutic approaches. AI algorithms create individualised treatment regimens by analyzing patient data, including genetics, biomarkers, and information on therapy response. This maximizes treatment efficacy and minimizes side effects. Additionally, wearable technology and remote monitoring devices powered by AI allow for real-time monitoring and intervention, improving patient safety and lowering hospital readmissions. Examines how AI has affected medical imaging. Radiologists' efficiency and accuracy in identifying anomalies are increased by deep learning algorithms' analysis of complicated medical pictures like CT scans and MRIs. As a result, diagnoses are made more quickly and accurately, allowing for quicker interventions and better patient outcomes. The fourth chapter examines how AI streamlines medical procedures. Administrative responsibilities are reduced and errors are minimized by automating operations like appointment scheduling and documentation. By offering timely support and triaging symptoms, intelligent catboats and virtual assistants increase patient involvement and happiness. The fifth segment talks with ethical issues related to AI in healthcare. In order to create and use AI algorithms responsibly, patient privacy, data security, and bias mitigation are essential. Fair and equitable healthcare practices must be ensured by ethical standards and legal requirements. The abstract wraps off with a preview of the potential effects of AI on healthcare delivery in the future. Emerging medical technologies including telemedicine, robotics, predictive analytics, and AI-assisted surgery show immense promise for revolutionizing the industry. To overcome obstacles, maximize advantages, and guarantee a human-centric approach in the integration of AI in healthcare, cooperation between healthcare practitioners, technologists, policymakers, and ethicists is essential.

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Section: A Glimpse Into the Future: Ai's Impact On Healthcare Deliverymentioning

confidence: 99%

The Future of Medicine: Harnessing the Power of AI for Revolutionizing Healthcare

Harry¹

2023

ijmdsa

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show abstract

“…These models can help with illness prevention, early disease identification, and the execution of focused therapies. For instance, depending on genetic markers, lifestyle factors, and biomarkers, AI systems can forecast a person's likelihood of developing cardiovascular disease, enabling healthcare professionals to use individualized preventative methods [16]. By examining huge amounts of medical literature, data from clinical trials, and patient information, AI has the potential to improve therapy choices in precision medicine.…”

Section: Leveraging Ai For Precision Medicinementioning

confidence: 99%

Transforming Healthcare through AI: Unleashing the Power of Personalized Medicine

Khan¹

2023

ijmdsa

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The healthcare sector now places a lot of emphasis on providing patients with personalized care that is catered to their unique requirements and features. A significant force behind the development and use of customized healthcare is artificial intelligence (AI). This essay examines the use of AI in personalized healthcare and how it can affect several facets of healthcare provision. The study starts out by talking about how AI is being used in diagnostics, emphasizing how machine learning algorithms and the examination of various datasets can improve diagnostic accuracy. It goes into more detail about how AI can be used to create tailored treatment plans, utilizing patient-specific data and predictive analytics to maximize therapeutic results and reduce side effects. Examined are the ethical issues surrounding AI in customized healthcare, such as data privacy, algorithmic bias, and the value of responsibility and openness. The integration of AI into clinical practice is also covered in the study, along with prospects for improving decision-making, streamlining workflow, and overall healthcare delivery effectiveness. The healthcare sector now places a lot of emphasis on providing patients with personalized care that is catered to their unique requirements and features. A significant force behind the development and use of customized healthcare is artificial intelligence (AI). This essay examines the use of AI in personalized healthcare and how it can affect several facets of healthcare provision. The study starts out by talking about how AI is being used in diagnostics, emphasizing how machine learning algorithms and the examination of various datasets can improve diagnostic accuracy. It goes into more detail about how AI can be used to create tailored treatment plans, utilizing patient-specific data and predictive analytics to maximize therapeutic results and reduce side effects. Examined are the ethical issues surrounding AI in customized healthcare, such as data privacy, algorithmic bias, and the value of responsibility and openness. The integration of AI into clinical practice is also covered in the study, along with prospects for improving decision-making, streamlining workflow, and overall healthcare delivery effectiveness.

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“…While SAS schemes offer pervasive and accurate information retrieval in critical scenarios, they still require dedicated UAVs, which are expensive and scarce resources having limited flight times Rashid et al (2021). On the other hand, vehicular sensor networks (VSNs) have matured into a dependable networked sensing paradigm for vigilance and situational awareness along roadways that uses cars equipped with physical sensors (e.g., dashboard cameras) to opportunistically identify event occurrences (e.g., accidents on roads) (Zhang et al, 2008).…”

Section: State-of-the-art Sps Applicationsmentioning

confidence: 99%

A survey on social-physical sensing: An emerging sensing paradigm that explores the collective intelligence of humans and machines

Rashid

Wei

Wang

2023

Collective Intelligence

Self Cite

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Propelled by the omnipresence of versatile data capture, communication, and computing technologies, physical sensing has revolutionized the avenue for decisively interpreting the real world. However, various limitations hinder physical sensing’s effectiveness in critical scenarios such as disaster response and urban anomaly detection. Meanwhile, social sensing is contriving as a pervasive sensing paradigm leveraging observations from human participants equipped with portable devices and ubiquitous Internet connectivity to perceive the environment. Despite its virtues, social sensing also inherently suffers from a few drawbacks (e.g., inconsistent reliability and uncertain data provenance). Motivated by the complementary strengths of the two sensing modes, social-physical sensing (SPS) is protruding as an emerging sensing paradigm that explores the collective intelligence of humans and machines to reconstruct the “state of the world,” both physically and socially. While a good number of interesting SPS applications have been studied, several critical unsolved challenges still exist in SPS. In this paper, we provide a comprehensive survey of SPS, emphasizing its definition, key enablers, state-of-the-art applications, potential research challenges, and roadmap for future work. This paper intends to bridge the knowledge gap of existing sensing-focused survey papers by thoroughly examining the various aspects of SPS crucial for building potent SPS systems.

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HeteroSAS: A Heterogeneous Resource Management Framework for "All-in-the-Air" Social Airborne Sensing in Disaster Response

Cited by 5 publications

References 31 publications

The Future of Medicine: Harnessing the Power of AI for Revolutionizing Healthcare

The Future of Medicine: Harnessing the Power of AI for Revolutionizing Healthcare

Transforming Healthcare through AI: Unleashing the Power of Personalized Medicine

A survey on social-physical sensing: An emerging sensing paradigm that explores the collective intelligence of humans and machines

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