Sustainable adsorptive removal of high concentration organic contaminants from water using biodegradable Gum-Acacia integrated magnetite nanoparticles hydrogel adsorbent

Khan, Muhammad Farooq; Ahmed, Haron; Almashhadani, Haider Abdulkareem; Al‐Bahrani, Mohammed; Khan, Asif; Ali, Sharafat; Gul, Noor; Hassan, Tajamul; Ismail, Ahmed E.; Zahid, Muhammad

doi:10.1016/j.inoche.2022.110057

Cited by 14 publications

(4 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similarly, a team of researchers at the University of Michigan developed an AI algorithm that can predict which patients are most likely to develop sepsis, a potentially life-threatening condition that can occur in response to an infection (Abed et al, 2022)[41,42]. The algorithm was trained on a dataset of more than 130,000 patient records and achieved an accuracy of 90% (Khan et al, 2022) (Sridhar et al, 2022).…”

Section: Electronic Health Records (Ehrs)mentioning

confidence: 99%

Artificial Intelligence in Health Sector of USA

Pendy¹

2023

JISS

View full text Add to dashboard Cite

The article describes how AI has already made a significant impact in the health sector in the US, with many promising future applications. In medical imaging, for example, AI algorithms have been developed that can detect and classify anomalies with high accuracy rates, potentially reducing the need for unnecessary biopsies or surgeries. Personalized medicine is another area where AI is being used to analyze large amounts of patient data and provide tailored treatments. AI is also being used to improve the accuracy and efficiency of electronic health records (EHRs) by automatically detecting errors and inconsistencies. In drug discovery, AI algorithms can analyze large data sets and predict which compounds are likely to be effective in treating a particular disease, potentially reducing the time and cost of drug development. In the future, AI is expected to play an even greater role in precision medicine, enabling clinicians to develop customized treatment plans based on a patient's individual genetic and medical history. AI is also being developed for use in virtual assistants, which can provide patients with personalized health advice and reminders. Clinical decision support systems are another area where AI is expected to have a significant impact, helping clinicians to make more informed decisions by analyzing patient data and providing recommendations based on the latest research and best practices. Overall, the article suggests that AI has the potential to transform healthcare by improving patient outcomes, reducing costs, and increasing access to care. However, the article also acknowledges that there are challenges to be addressed, such as ensuring the accuracy and fairness of AI algorithms and addressing privacy concerns.

show abstract

Section: Electronic Health Records (Ehrs)mentioning

confidence: 99%

Artificial Intelligence in Health Sector of USA

Pendy¹

2023

JISS

View full text Add to dashboard Cite

show abstract

“…AI in education refers to the use of artificial intelligence technologies, such as machine learning and natural language processing, to enhance the learning experience (Alneyadi et al, 2023). It involves the use of algorithms that analyze data, identify patterns, and make predictions, enabling educators to personalize learning for each student (Khan et al, 2022). The potential benefits of using AI in education are significant.…”

Section: Introductionmentioning

confidence: 99%

Role of AI in Education

Harry

2023

Injurity

View full text Add to dashboard Cite

Artificial intelligence (AI) has the potential to revolutionize the way we learn and teach, making it more personalized, engaging, and efficient. AI in education refers to the use of artificial intelligence technologies, such as machine learning and natural language processing, to enhance the learning experience. It involves the use of algorithms that analyze data, identify patterns, and make predictions, enabling educators to personalize learning for each student. The potential benefits of using AI in education are significant. Personalized learning, one of the most significant advantages of AI in education, can lead to better student outcomes, as students can learn at their own pace and in a way that suits their learning style. Intelligent tutoring systems, chatbots, and automated grading and assessment can increase efficiency, save teachers' time, and provide more accurate and consistent feedback. However, there are also challenges associated with using AI in education. Privacy and security concerns, lack of trust, cost, and potential bias are some of the challenges that need to be addressed. Ethical considerations such as ensuring accessibility, transparency, and fairness in AI-based education systems also need to be taken into account. Despite these challenges, the potential of AI in education is immense. AI can provide better data analysis, enabling educators to make data-driven decisions. In this review we described role of AI in management, promotion of education which describe the effect of AI in education sector

show abstract

“…Magnetic composite hydrogels exhibit uniform dispersion of magnetic nanoparticles, enabling responsive behaviors such as movement, [1][2][3] stretching, 4 and heating. 5,6 These properties hold tremendous potential for applications in pollution treatment, [7][8][9][10] bionic intelligence, [11][12][13][14] and drug-sustained release and targeted drug delivery. [15][16][17] However, challenges persist in the preparation and mechanical properties of magnetic composite hydrogels, impeding their widespread adoption and development.…”

Section: Introductionmentioning

confidence: 99%

Preparation of graphene oxide enhanced magnetic composite hydrogels by one‐pot method for selective adsorption

Yan,

Liu,

Yang

et al. 2023

J of Applied Polymer Sci

View full text Add to dashboard Cite

Magnetic composite hydrogels exhibit promising prospects for diverse applications, but their mechanical properties impose limitations on their further advancement. In this study, a novel approach is proposed to directly prepare magnetic composite hydrogels utilizing nanoferroferric oxide, aiming to replace the existing preparation method. Meanwhile, graphene oxide (GO) is introduced into magnetic composite hydrogels to enhance their mechanical characteristics. By employing ammonium citrate (AC) as a dispersant, the dispersion of ferroferric oxide magnetic nanoparticles at a concentration of 40 mg/mL is achieved, enabling their coexistence with GO for the preparation of magnetic composite hydrogels. Notably, the incorporation of 3 mg/mL GO and 40 mg/mL magnetic nanoparticles in polyacrylamide (PAM) hydrogel yields remarkable improvements in maximum stress and strain, reaching 148 kPa and 496%, respectively. In contrast, magnetic composite hydrogels without GO exhibit lower values of 46.5 kPa and 351%. The presence of magnetic nanoparticles imparts magnetism to the hydrogel, with higher concentrations of magnetic nanoparticles leading to increased magnetism. Moreover, the presence of AC and GO renders the hydrogels electronegative, thereby endowing them with selective adsorption capabilities. In summary, the magnetic composite hydrogels prepared by one‐pot method have good mechanical properties and selective adsorption capacity, and have good application potential.

show abstract

Sustainable adsorptive removal of high concentration organic contaminants from water using biodegradable Gum-Acacia integrated magnetite nanoparticles hydrogel adsorbent

Cited by 14 publications

References 35 publications

Artificial Intelligence in Health Sector of USA

Artificial Intelligence in Health Sector of USA

Role of AI in Education

Preparation of graphene oxide enhanced magnetic composite hydrogels by one‐pot method for selective adsorption

Contact Info

Product

Resources

About