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Computers in Biology and Medicine Jul 2022The exact nature, harmful effects and aetiology of autism spectrum disorder (ASD) have caused widespread confusion. Artificial intelligence (AI) science helps solve...
The exact nature, harmful effects and aetiology of autism spectrum disorder (ASD) have caused widespread confusion. Artificial intelligence (AI) science helps solve challenging diagnostic problems in the medical field through extensive experiments. Disease severity is closely related to triage decisions and prioritisation contexts in medicine because both have been widely used to diagnose various diseases via AI, machine learning and automated decision-making techniques. Recently, taking advantage of high-performance AI algorithms has achieved accessible success in diagnosing and predicting risks from clinical and biological data. In contrast, less progress has been made with ASD because of obscure reasons. According to academic literature, ASD diagnosis works from a specific perspective, and much of the confusion arises from the fact that how AI techniques are currently integrated with the diagnosis of ASD concerning the triage and priority strategies and gene contributions. To this end, this study sought to describe a systematic review of the literature to assess the respective AI methods using the available datasets, highlight the tools and strategies used for diagnosing ASD and investigate how AI trends contribute in distinguishing triage and priority for ASD and gene contributions. Accordingly, this study checked the Science Direct, IEEE Xplore Digital Library, Web of Science (WoS), PubMed, and Scopus databases. A set of 363 articles from 2017 to 2022 is collected to reveal a clear picture and a better understanding of all the academic literature through a final set of 18 articles. The retrieved articles were filtered according to the defined inclusion and exclusion criteria and classified into three categories. The first category includes 'Triage patients based on diagnosis methods' which accounts for 16.66% (n = 3/18). The second category includes 'Prioritisation for Risky Genes' which accounts for 66.6% (n = 12/18) and is classified into two subcategories: 'Mutations observation based', 'Biomarkers and toxic chemical observations'. The third category includes 'E-triage using telehealth' which accounts for 16.66% (n = 3/18). This multidisciplinary systematic review revealed the taxonomy, motivations, recommendations and challenges of ASD research that need synergistic attention. Thus, this systematic review performs a comprehensive science mapping analysis and discusses the open issues that help perform and improve the recommended solution of ASD research direction. In addition, this study critically reviews the literature and attempts to address the current research gaps in knowledge and highlights weaknesses that require further research. Finally, a new developed methodology has been suggested as future work for triaging and prioritising ASD patients according to their severity levels by using decision-making techniques.
Topics: Artificial Intelligence; Autism Spectrum Disorder; Humans; Machine Learning; Telemedicine; Triage
PubMed: 35561591
DOI: 10.1016/j.compbiomed.2022.105553 -
AJNR. American Journal of Neuroradiology Jan 2017Ultrasound has become widely accepted as the first imaging technique used for the assessment of cervical lymph node metastasis in patients with papillary thyroid cancer.... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND AND PURPOSE
Ultrasound has become widely accepted as the first imaging technique used for the assessment of cervical lymph node metastasis in patients with papillary thyroid cancer. In this systematic review and meta-analysis, we evaluate the performance of CT for the preoperative diagnosis of cervical lymph node metastasis in patients with papillary thyroid cancer compared with ultrasound.
MATERIALS AND METHODS
Ovid-MEDLINE and EMBASE data bases were searched for studies regarding the use of CT to diagnose cervical lymph node metastasis. The diagnostic performance of CT, ultrasound, and combined CT/ultrasound was assessed by using level-by-level and patient-based analyses. We also performed meta-analyses on the basis of the central and lateral neck levels.
RESULTS
Nine eligible studies, including a total sample size of 1691 patients, were included. CT showed a summary sensitivity of 62% (95% CI, 52%-70%) and specificity of 87% (95% CI, 80%-92%) for diagnosing cervical lymph node metastasis when using level-by-level analysis. There was a positive correlation between the sensitivity and the false-positive rate (correlation coefficient, 0.807) because of the threshold effect. The summary sensitivity of combined CT/ultrasound (69%; 95% CI, 61%-77%) was significantly higher than ultrasound (51%; 95% CI, 42%-60%), though the summary specificity did not differ.
CONCLUSIONS
The diagnostic performances of CT and ultrasound are similar, though CT and ultrasound combined are superior to ultrasound only. CT may be used as a complementary diagnostic method in addition to ultrasound for diagnosing cervical lymph node metastasis in patients with papillary thyroid cancer.
Topics: Adult; Carcinoma, Papillary; Female; Humans; Lymphatic Metastasis; Sensitivity and Specificity; Thyroid Cancer, Papillary; Thyroid Neoplasms; Tomography, X-Ray Computed
PubMed: 27789450
DOI: 10.3174/ajnr.A4967 -
Diagnostic and Interventional Radiology... Nov 2021Bone tracers have been validated for many years in detecting transthyretin cardiac amyloidosis (TTR-CA). However, several new studies suggest conflicting results. Our... (Meta-Analysis)
Meta-Analysis
PURPOSE
Bone tracers have been validated for many years in detecting transthyretin cardiac amyloidosis (TTR-CA). However, several new studies suggest conflicting results. Our study aimed to systematically evaluate the accuracy of bone radiotracers for diagnosis and differentiation of TTR-CA via a systematic review and meta-analysis.
METHODS
We retrieved articles assessing the performance of bone tracer in diagnosing and differentiating TTR-CA from PubMed, the Cochrane Library, ScienceDirect, and DOAJ databases, dating up to 10 July 2020. The meta-analysis was conducted through Stata 16 software, and the risk of bias for the included studies was assessed by the QUADAS-2 tool. Moreover, we made a comprehensive review.
RESULTS
Fourteen articles were included in the systematic review, and 9 in the meta-analysis. The pooled sensitivity was 0.97 (95% confidence interval [95% CI] 0.85-0.99) with heterogeneity (I2=73.5, 95% CI 55.6-91.2), and the specificity was 0.92 (95% CI 0.82-0.96) with heterogeneity (I2=42.0, 95% CI 0.0-86.9). The pooled positive and negative likelihood ratios were 11.49 (95% CI 5.07-26.0) and 0.03 (95% CI 0.01-0.18), respectively. The diagnostic odds ratio was 341 (95% CI 53-2194), and the area under the receiver operating characteristic curve was 0.96 (95% CI 0.94-0.97).
CONCLUSION
The findings evidence that the bone radiotracer is a valuable noninvasive approach that provides high accuracy for diagnosing TTR-CA and plays a modest role in differentiating TTR-CA from immunoglobulin amyloid light-chain cardiac amyloidosis. 99mTc-HMDP may be more accurate than 99mTc-PYP, 99mTc-DPD, and 18F-NaF in the TTR-CA detecting process, and 18F-NaF is a promising bone tracer to diagnose and differentiate TTR-CA.
Topics: Amyloidosis; Bone and Bones; Heart; Humans; Prealbumin; Radionuclide Imaging
PubMed: 34792038
DOI: 10.5152/dir.2021.20662 -
Journal of Stroke and Cerebrovascular... Nov 2023Stroke diagnosis is dependent on lengthy clinical and neuroimaging assessments, while rapid treatment initiation improves clinical outcome. Currently, more sensitive... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Stroke diagnosis is dependent on lengthy clinical and neuroimaging assessments, while rapid treatment initiation improves clinical outcome. Currently, more sensitive biomarker assays of both non-coding RNA- and protein biomarkers have improved their detectability, which could accelerate stroke diagnosis. This systematic review and meta-analysis compares non-coding RNA- with protein biomarkers for their potential to diagnose and differentiate acute stroke (subtypes) in (pre-)hospital settings.
METHODS
We performed a systematic review and meta-analysis of studies evaluating diagnostic performance of non-coding RNA- and protein biomarkers to differentiate acute ischemic and hemorrhagic stroke, stroke mimics, and (healthy) controls. Quality appraisal of individual studies was assessed using the QUADAS-2 tool while the meta-analysis was performed with the sROC approach and by assessing pooled sensitivity and specificity, diagnostic odds ratios, positive- and negative likelihood ratios, and the Youden Index.
SUMMARY OF REVIEW
112 studies were included in the systematic review and 42 studies in the meta-analysis containing 11627 patients with ischemic strokes, 2110 patients with hemorrhagic strokes, 1393 patients with a stroke mimic, and 5548 healthy controls. Proteins (IL-6 and S100 calcium-binding protein B (S100B)) and microRNAs (miR-30a) have similar performance in ischemic stroke diagnosis. To differentiate between ischemic- or hemorrhagic strokes, glial fibrillary acidic protein (GFAP) levels and autoantibodies to the NR2 peptide (NR2aAb, a cleavage product of NMDA neuroreceptors) were best performing whereas no investigated protein or non-coding RNA biomarkers differentiated stroke from stroke mimics with high diagnostic potential.
CONCLUSIONS
Despite sampling time differences, circulating microRNAs (< 24 h) and proteins (< 4,5 h) perform equally well in ischemic stroke diagnosis. GFAP differentiates stroke subtypes, while a biomarker panel of GFAP and UCH-L1 improved the sensitivity and specificity of UCH-L1 alone to differentiate stroke.
Topics: Humans; Hemorrhagic Stroke; Stroke; Biomarkers; Ischemic Stroke; Glial Fibrillary Acidic Protein; MicroRNAs; RNA, Untranslated
PubMed: 37778160
DOI: 10.1016/j.jstrokecerebrovasdis.2023.107388 -
Journal of Hospital Medicine Mar 2023There is no gold standard test to accurately identify patients with cellulitis and therefore misdiagnosis is common. Using the clinical impression of a dermatology or an... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
There is no gold standard test to accurately identify patients with cellulitis and therefore misdiagnosis is common. Using the clinical impression of a dermatology or an infectious disease specialist as a reference standard, we sought to determine the prevalence of misdiagnosis of cellulitis among nonspecialist physicians.
METHODS
A systemic search was performed using MEDLINE, Cochrane Library, and EMBASE databases for studies reporting diagnostic accuracy of cellulitis. Inclusion criteria required dermatology or infectious disease consultation for all patients diagnosed with cellulitis by generalist physicians. We used random effects modeling to estimate the prevalence of misdiagnosis using consultant diagnosis as a reference standard.
RESULTS
Eight studies contributed to the analysis. For the seven studies involving inpatients, the results were sufficiently homogeneous to justify pooling data. Of 858 inpatients initially diagnosed with cellulitis, 335 (39%, 95% confidence interval: 31-47) received an alternative diagnosis from the specialist. Heterogeneity was large (I = 74%) and the greatest contributor to between-study variance was the year of publication. Alternative diagnoses were mostly noninfectious (68%, 221/327), with stasis dermatitis (18%, 60/327) being the most common. An abscess was the most common alternative infectious diagnosis (10%, 32/327).
DISCUSSION
Cellulitis is commonly misdiagnosed among inpatients, leading to unnecessary hospital admissions and antibiotic overuse. Most alternative diagnoses are noninfectious. Continuing medical education among general practitioners and urgent care providers will likely reduce cellulitis misdiagnoses.
Topics: Humans; Cellulitis; Prevalence; Anti-Bacterial Agents; Diagnostic Errors; Communicable Diseases
PubMed: 36189619
DOI: 10.1002/jhm.12977 -
Multiple Sclerosis and Related Disorders Mar 2022In recent years Artificial intelligence (AI) techniques are rapidly evolving into clinical practices such as diagnosis and prognosis processes, assess treatment... (Review)
Review
BACKGROUND
In recent years Artificial intelligence (AI) techniques are rapidly evolving into clinical practices such as diagnosis and prognosis processes, assess treatment effectiveness, and monitoring of diseases. The previous studies showed interesting results regarding the diagnostic efficiency of AI methods in differentiating Multiple sclerosis (MS) patients from healthy controls or other demyelinating diseases. There is a great lack of a comprehensive systematic review study on the role of AI in the diagnosis of MS. We aimed to perform a systematic review to document the performance of AI in MS diagnosis.
METHODS
A systematic search was performed using four databases including PubMed, Scopus, Web of Science, and IEEE on August 2021. All original studies which focused on deep learning or AI to analyze any modalities with the purpose of diagnosing MS were included in our study.
RESULTS
Finally, 38 studies were included in our systematic review after the abstract and full-text screening. A total of 5433 individuals were included, including 2924 cases of MS and 2509 healthy controls. Sensitivity and specificity were reported in 29 studies which ranged from 76.92 to 100 for sensitivity and 74 to 100 for specificity. Furthermore, 34 studies reported accuracy ranged 81 to 100. Among included studies, Magnetic Resonance Imaging (MRI) (20 studies), OCT (six studies), serum and cerebrospinal fluid markers (six studies), movement function (three studies), and other modalities such as breathing and evoked potential was used for detecting MS via AI.
CONCLUSION
In conclusion, diagnosis of MS based on new markers and AI is a growing field of research with MRI images, followed by images obtained from OCT, serum and CSF biomarkers, and motor associated markers. All of these results show that with advances made in AI, the way we monitor and diagnose our MS patients can change drastically.
Topics: Artificial Intelligence; Humans; Magnetic Resonance Imaging; Multiple Sclerosis
PubMed: 35180619
DOI: 10.1016/j.msard.2022.103673 -
Clinical Endocrinology May 2019Saline infusion test (SIT), captopril challenge test (CCT), fludrocortisone suppression test (FST) and oral sodium loading test (SLT) are recommended by the Endocrine... (Meta-Analysis)
Meta-Analysis
OBJECTIVE
Saline infusion test (SIT), captopril challenge test (CCT), fludrocortisone suppression test (FST) and oral sodium loading test (SLT) are recommended by the Endocrine Society's Clinical Practice Guidelines to diagnose primary aldosteronism, but which one is the best remains controversial. We aimed to summarize the available comparative data and evaluate the diagnostic accuracy of these four tests.
DESIGN
We searched PubMed, Embase and the Cochrane Library for relevant studies published between January 1980 and January 2018.
PATIENTS
Eligible studies reported on the accuracy of one or more of the four confirmatory tests in patients suspected of PA.
MEASUREMENTS
Two reviewers independently conducted the data extraction of all selected studies, which consisted of study characteristics and data to estimate the summary receiver operating characteristic (SROC) curve and the corresponding summary area under the curve (SAUC), pooled sensitivity and specificity, diagnostic odds ratios (DOR) with 95% confidence interval (CI).
RESULTS
We identified 26 articles including 3686 patients. Fifteen articles evaluated the diagnostic accuracy of CCT, 10 of SIT, 1 of FST and none of SLT. For CCT, the SAUC was 0.9207, and the pooled sensitivity and specificity were 0.87 (95% CI: 0.84-0.89) and 0.84 (95% CI: 0.81-0.86), respectively. For SIT, the SAUC was 0.9232, and the pooled sensitivity and specificity were 0.85 (95% CI: 0.82-0.87) and 0.87 (95% CI: 0.85-0.89), respectively. For FST, the pooled sensitivity and specificity were 0.87 (95% CI: 0.66-0.97) and 0.95 (95% CI: 0.82-0.99), respectively. Overall, we found no significant differences in the diagnostic accuracy of CCT and SIT.
CONCLUSIONS
CCT and SIT exhibit high and comparable accuracy for diagnosing PA. CCT may be a more feasible alternative as it is safe and much easier to perform.
Topics: Diagnostic Techniques, Endocrine; Humans; Hyperaldosteronism
PubMed: 30721529
DOI: 10.1111/cen.13943 -
Spine May 2017A systematic review. (Review)
Review
STUDY DESIGN
A systematic review.
OBJECTIVE
The aim of this study was to provide an evidence-based recommendation for when and how to employ imaging studies when diagnosing back pain thought to be caused by spondylolysis in pediatric patients.
SUMMARY OF BACKGROUND DATA
Spondylolysis is a common structural cause of back pain in pediatric patients. The radiologic methods and algorithms used to diagnose spondylolysis are inconsistent among practitioners.
METHODS
A literature review was performed in PubMed and Cochrane databases using the search terms "spondylolysis," "pediatric," "adolescent," "juvenile," "young," "lumbar," "MRI," "bone scan," "CT," and "SPECT." After inclusion criteria were applied, 13 articles pertaining to diagnostic imaging of pediatric spondylolysis were analyzed.
RESULTS
Ten papers included sensitivity calculations for comparing imaging performance. The average sensitivity of magnetic resonance imaging (MRI) with computed tomography (CT) as the standard of reference was 81.4%. When compared with single-photon emission CT (SPECT), the average sensitivity of CT was 85% and the sensitivity of MRI was 80%. Thirteen studies made a recommendation as to how best to perform diagnostic imaging of patients with clinically suspected spondylolysis. When compared with two-view plain films, bone scans had seven to nine times the effective radiation dose, while four-view plain films and CT were approximately double. Of the diagnostic methods examined, MRI was the most expensive followed by CT, bone scan, four-view plain films, and two-view plain films.
CONCLUSION
Due to their efficacy, low cost, and low radiation exposure, we find two-view plain films to be the best initial study. With unusual presentations or refractory courses, practitioners should pursue advanced imaging. MRI should be used in early diagnosis and CT in more persistent courses. However, the lack of rigorous studies makes it difficult to formulate concrete recommendations.
LEVEL OF EVIDENCE
3.
Topics: Back Pain; Early Diagnosis; Humans; Magnetic Resonance Imaging; Pediatrics; Radiography; Spondylolysis
PubMed: 27669047
DOI: 10.1097/BRS.0000000000001912 -
AJR. American Journal of Roentgenology Nov 2022It is unclear which, MRI or ultrasound (US), is the most useful imaging tool to diagnose rotator cuff retears. The objective of this study was to evaluate MRI and US... (Meta-Analysis)
Meta-Analysis Review
It is unclear which, MRI or ultrasound (US), is the most useful imaging tool to diagnose rotator cuff retears. The objective of this study was to evaluate MRI and US in terms of diagnosing retear of a repaired rotator cuff tendon using a systematic review and meta-analysis. A comprehensive literature search was performed on the main concepts of MRI (including noncontrast MRI and MR arthrography), US, and rotator cuff repairs. Inclusion criteria consisted of original research studies that assessed the diagnostic accuracy of MRI and US (index tests) for the diagnosis of rotator cuff tendon retear after prior rotator cuff repair using surgical findings as the reference standard. QUADAS-2 was used to assess methodologic quality. Meta-analyses were performed to compare MRI and US studies in the diagnosis of all retears and of full-thickness retears. Study variation was analyzed using the Cochran test and statistic. Eight studies (MRI, = 6; US, = 2) satisfied inclusion and exclusion criteria, consisting of 304 total patients (MRI, = 221; US, = 83) and 309 shoulders (MRI, = 226; US, = 83). Years of publication ranged from 1993 to 2006 for the MRI studies and from 2003 to 2018 for the US studies. Two studies had high risk of bias in terms of applicability to clinical practice because of patient selection. Five studies had potential risk of bias in two categories, whereas two had potential risk of bias in three categories. For all retears, mean sensitivity and specificity for MRI were 81.4% (95% CI, 73.3-87.5%) and 82.6% (95% CI, 76.3-87.5%) and 83.7% (95% CI, 67.4-92.7%) and 90.7% (95% CI, 73.6-97.1%) for US. For full-thickness retears, mean sensitivity and specificity for MRI were 85.9% (95% CI, 80.2-90.2%) and 89.1% (95% CI, 84.6-92.4%) and 89.7% (95% CI, 75.6-96.1%) and 91.0% (95% CI, 75.5-97.1%) for US. There was no significant difference in terms of sensitivity or specificity for either comparison ( = .28-.76). Our analyses revealed no significant difference between US and MRI for the diagnosis of rotator cuff tendon tears after prior cuff repair. Either MRI or US can be considered a first-line imaging option to assess suspected rotator cuff retear after prior repair.
Topics: Humans; Rotator Cuff; Rotator Cuff Injuries; Arthrography; Ultrasonography; Magnetic Resonance Imaging; Arthroscopy; Treatment Outcome
PubMed: 35642759
DOI: 10.2214/AJR.22.27847 -
Atherosclerosis Dec 2020We aimed to compare the diagnostic accuracy of ankle brachial index (ABI) and toe brachial index (TBI) for peripheral arterial disease (PAD) in a wide spectrum of PAD... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND AND AIMS
We aimed to compare the diagnostic accuracy of ankle brachial index (ABI) and toe brachial index (TBI) for peripheral arterial disease (PAD) in a wide spectrum of PAD populations and reference standard tests, and to examine variables influencing heterogeneity in the estimates.
METHODS
Systematic searches in EMBASE, MEDLINE, Web of Science and the Cochrane Library databases were performed, from inception to January 2020. Hierarchical summary receiver operating characteristic curves (HSROC) were used to summarize the pooled test performance.
RESULTS
Thirty five (patient-level: 1318 patients, limb-level: 5637 limbs) and nine studies (patient-level: 294 patients, limb-level: 826 limbs) were included in ABI and TBI meta-analyses, respectively. The QUADAS-2 tool identified many studies with high risk of bias, especially in the "patient selection" domain. Pooled estimates for ABI in detecting 50% or greater stenosis were sensitivity = 61% (95% CI: 55-69), specificity = 92% (95% CI: 89-95) and dOR = 16.5 (95% CI: 11.5-23.6). Similarly, TBI yielded sensitivity = 81% (95% CI: 70-94), specificity = 77% (95% CI: 66-90) and dOR = 13.1 (95% CI: 7.0-24.8). In a direct comparison of seven studies jointly analyzing ABI and TBI, TBI showed better overall diagnostic accuracy (16.4 vs 11.0 in dOR) at the expense of sensitivity (82% vs 52%), while specificity (77% vs 94%) performed worse in TBI than ABI. Heterogeneity was large in sensitivity for ABI, with variables as different reference standard tests, smoking habit and PAD prevalence accounting for such variability. Similarly, gender, different index test cut-offs and sample size influenced the heterogeneity in TBI specificity.
CONCLUSIONS
Though ABI and TBI showed similar diagnostic performance to diagnose PAD, TBI showed far better sensitivity than ABI, especially in "challenging populations", as those exhibiting calcification.
Topics: Ankle Brachial Index; Humans; Lower Extremity; Peripheral Arterial Disease; ROC Curve
PubMed: 33036766
DOI: 10.1016/j.atherosclerosis.2020.09.026