Emerging Trends in Applying Artificial Intelligence to Monkeypox Disease: A Bibliometric Analysis

Applied Data Science and Analysis, Год журнала: 2024, Номер 2024, С. 148 - 164

Опубликована: Сен. 8, 2024

Monkeypox is a rather rare viral infectious disease that initially did not receive much attention but has recently become subject of concern from the point view public health. Artificial intelligence (AI) techniques are considered beneficial when it comes to diagnosis and identification through medical big data, including imaging other details patients’ information systems. Therefore, this work performs bibliometric analysis incorporate fields AI bibliometrics discuss trends future research opportunities in Monkeypox. A search over various databases was performed title abstracts articles were reviewed, resulting total 251 articles. After eliminating duplicates irrelevant papers, 108 found be suitable for study. In reviewing these studies, given on who contributed topics or fields, what new appeared time, papers most notable. The main added value outline reader process how conduct correct comprehensive by examining real case study related disease. As result, shows great potential improve diagnostics, treatment, health recommendations connected with Possibly, application can enhance responses outcomes since hasten effective interventions.

Язык: Английский

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Multicriteria Decision-Making Framework for Robust Energy Management Ai Solutions

Опубликована: Янв. 1, 2024

Язык: Английский

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Predictive value of POSSUM scoring system for postoperative complications and mortality in elderly patients with colorectal cancer

Technology and Health Care, Год журнала: 2024, Номер 32(6), С. 4653 - 4660

Опубликована: Авг. 2, 2024

BACKGROUND: The POSSUM scoring system, widely employed in assessing surgical risks, offers a simplified and objective approach for the prediction of complications mortality patient. Despite its effectiveness various fields, including orthopedics cardiovascular surgery, yet utilization elderly patients undergoing colorectal cancer surgery is infrequent. OBJECTIVE: To analyze predictive value system postoperative with cancer. METHODS: 306 were grouped according to death within 30 days after surgery. Among them, 108 cases complication group, 198 non-complication 16 group 290 survival group. scores all subjects obtained was conducted by ROC curve. RESULTS: No apparent difference observed among different disease types, operation types timing (P> 0.05). R2 higher than (P< R1 AUC predicting 0.955 sensitivity 88.89% specificity 94.44% evaluating 0.783 56.25% 82.93%. CONCLUSION: score has certain However, predicted rate actual rate.

Язык: Английский

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Proportional Neutrosophic CODAS Method and Its Application to Electric Vehicle Station Location Selection

Lecture notes in networks and systems, Год журнала: 2024, Номер unknown, С. 766 - 774

Опубликована: Янв. 1, 2024

Язык: Английский

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Reliability analysis for patient safety in the healthcare sector using dual hesitant pythagorean fuzzy set

Life Cycle Reliability and Safety Engineering, Год журнала: 2024, Номер unknown

Опубликована: Окт. 21, 2024

Язык: Английский

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