Preventing respiratory failure is crucial in a large proportion of COVID-19 patients infected with SARS-CoV-2 virus pneumonia termed as Novel Coronavirus Pneumonia (NCP). Rapid diagnosis and detection of high-risk patients for effective interventions have been shown to be troublesome. Using a large, computed tomography (CT) database, we developed an artificial intelligence (AI) parameter to diagnose NCP and distinguish it from other kinds of pneumonia and traditional controls. The literature was studied and analyzed from diverse assets which include Scopus, Nature medicine, IEEE, Google scholar, Wiley Library, and PubMed. The search terms used were 'COVID-19', 'AI', 'diagnosis', and 'prognosis'. To strengthen the overall performance of AI in COVID-19 diagnosis and prognosis, we segregated several components to perceive threats and opportunities, as well as their inter-dependencies that affect the healthcare sector. This paper seeks to pick out the crucial fulfillment of factors for AI with inside the healthcare sector in the Indian context. Using critical literature review and experts' opinion, a total of 11 factors affecting COVID-19 diagnosis and prognosis were detected, and we eventually used an interpretive structural model (ISM) to build a framework of interrelationships among the identified factors. Finally, the matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) analysis resulted the driving and dependence powers of these identified factors. Our analysis will help healthcare stakeholders to realize the requirements for successful implementation of AI.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8471992 | PMC |
| http://dx.doi.org/10.3390/diagnostics11091604 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Objective: This study aims to investigate the relationship between preoperative cervical intervertebral foramen width and area and the persistence of postoperative pain in patients diagnosed with cervical spondylotic radiculopathy (CSR).
Methods: Patients were divided into two groups, based on their pain relief at the 6-month postoperative follow-up: the pain relief group and the persistent pain group. We compared various parameters, including age, sex, body mass index (BMI), duration of symptoms, preoperative Japanese Orthopedic Association (JOA) score, Neck Disability Index (NDI) score, postoperative ratio of disc space distraction, preoperative width of the intervertebral foramen (WIVF), and area of the intervertebral foramen (AIVF) between the two groups.
High anti-Müllerian hormone level as a predictor of poor pregnancy outcomes in women with polycystic ovary syndrome undergoing in vitro fertilization/intracytoplasmic sperm injection: a retrospective cohort study.
Reprod Biol Endocrinol
January 2025
Department of Obstetrics and Gynecology, Center for Reproductive Medicine, Peking University Third Hospital, Beijing, 100191, China.
Objective: To study the correlation between anti-Müllerian hormone levels and pregnancy outcomes after in vitro fertilization/intracytoplasmic sperm injection in women with polycystic ovary syndrome, which remains controversial.
Methods: This retrospective cohort study recruited 4,719 women with infertility and polycystic ovary syndrome aged 20-40 years who underwent treatment at the Reproductive Center of Peking University Third Hospital between February 2017 and June 2023. We divided the participants into three groups according to the 25th and 75th percentile cutoffs of serum anti-Müllerian hormone: low (≤ 4.
Establishing a preoperative predictive model for gallbladder adenoma and cholesterol polyps based on machine learning: a multicentre retrospective study.
World J Surg Oncol
January 2025
Department of Hepatobiliary and Pancreas, Affiliated Hospital of Qingdao University, NO.1677 Wutaishan Road, Qingdao, Shandong Province, 266555, China.
Background: With the rising diagnostic rate of gallbladder polypoid lesions (GPLs), differentiating benign cholesterol polyps from gallbladder adenomas with a higher preoperative malignancy risk is crucial. This study aimed to establish a preoperative prediction model capable of accurately distinguishing between gallbladder adenomas and cholesterol polyps using machine learning algorithms.
Materials And Methods: We retrospectively analysed the patients' clinical baseline data, serological indicators, and ultrasound imaging data.
Predictive role of SLC1A5 in neuroblastoma prognosis and immunotherapy.
BMC Cancer
January 2025
Department of Pediatric Surgery, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Background: Neuroblastoma, a prevalent extracranial solid tumor in pediatric patients, demonstrates significant clinical heterogeneity, ranging from spontaneous regression to aggressive metastatic disease. Despite advances in treatment, high-risk neuroblastoma remains associated with poor survival. SLC1A5, a key glutamine transporter, plays a dual role in promoting tumor growth and immune modulation.
View Article and Find Full Text PDFHyponatremia is associated with malignant brain edema after mechanical thrombectomy in acute ischemic stroke.
BMC Neurol
January 2025
Neurological Disorder Center, Department of Cerebrovascular Disease, Suining Central Hospital, Sichuan, 629000, China.
Background: Hyponatremia (< 135 mmol/L) is the most common electrolyte disturbance in patients with stroke. However, few studies have reported the relationship between hyponatremia at admission and outcomes in patients with acute ischemic stroke (AIS) treated with mechanical thrombectomy (MT). This study is aimed to explore the association between hyponatremia and clinical outcomes following MT.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!