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class="site-content" id="content"> <div class="content-area" id="primary"> <main class="site-main" id="main"> <article id="post-85" class="post-85 post type-post status-publish format-standard has-post-thumbnail hentry category-pediatric-epilepsy tag-artificial-intelligence tag-data-analytics tag-epilepsy tag-epilepsy-diagnosis tag-epilepsy-symptoms tag-genetic-testing tag-neurodegenerative-disorder tag-neurological tag-neurological-disorder tag-neurostimulation tag-paediatric-neurologist tag-smart-implants" itemtype="https://schema.org/CreativeWork" itemscope> <div class="inside-article"> <div class="featured-image page-header-image-single "> <img width="800" height="419" src="https://neonataldisorders.com/archive/wp-content/uploads/2024/10/banner-7-1-01.jpg" class="attachment-full size-full" alt="" itemprop="image" decoding="async" fetchpriority="high" srcset="https://neonataldisorders.com/archive/wp-content/uploads/2024/10/banner-7-1-01.jpg 800w, https://neonataldisorders.com/archive/wp-content/uploads/2024/10/banner-7-1-01-300x157.jpg 300w, https://neonataldisorders.com/archive/wp-content/uploads/2024/10/banner-7-1-01-768x402.jpg 768w" sizes="(max-width: 800px) 100vw, 800px" /> </div> <header class="entry-header"> <h1 class="entry-title" itemprop="headline">Technological Innovations in Pediatric Epilepsy Diagnosis</h1> <div class="entry-meta"> <span class="posted-on"><time class="entry-date published" datetime="2024-10-08T18:55:46+05:30" itemprop="datePublished">October 8, 2024</time></span> <span class="byline">by <span class="author vcard" itemprop="author" itemtype="https://schema.org/Person" itemscope><a class="url fn n" href="https://neonataldisorders.com/archive/author/neonataldisorders/" title="View all posts by neonataldisorders" rel="author" itemprop="url"><span class="author-name" itemprop="name">neonataldisorders</span></a></span></span> </div> </header> <div class="entry-content" itemprop="text"> <p><span style="font-weight: 400;">Epilepsy is a chronic neurological condition that is truly worldwide, affecting close to 10% of children in the world. This is defined by either recurring seizures or one major seizure, seeing that seizures are momentary disturbances of brain function caused by cerebral electrical events. Epilepsy in children can often be misdiagnosed, mainly because the symptoms are not as conspicuous as in adults, and interpreting tests such as electroencephalograms (EEG). In the last few years, with the help of artificial intelligence and machine learning, approaches to pediatric epilepsy diagnosis have completely changed. By supporting more precise, prompt, and non-ruptive means to detect seizure-related abnormalities in kids, these technologies promise better control or therapeutic approaches to handling these structural abnormalities. </span></p> <p><span style="font-weight: 400;">Machine learning in the diagnostics of pediatric epilepsy can be considered the start of an epoch of value-based medicine. Conventional diagnosis of epilepsy used to involve the identification of epileptic activity on the raw EEG records by clinical specialists. However, this is a very time-consuming technique and not always accurate, especially in some other complicated issues. At the moment, hard work is being done to create smarter algorithms that would improve and simplify the process of analyzing the EEG. For instance, current deep learning strategies have learned to identify patterns in EEG signals that can go unnoticed by human employees. Such patterns mostly help to reveal the nature and place of epilepsy for further treatment. </span></p> <p></div></div> <div style="background: #f7f7f7;border: 1px solid rgba(0, 0, 0, 0.07);"> <div style="padding: 30px;"><div class="Adblock-main"> <div class="Adblock-head"> <h2>Yearwise Publication Trend on <b>“<a href="https://neonataldisorders.com/publication-trends/index/pediatric epilepsy" target="_blank" title="pediatric epilepsy - yearwise publication trends">pediatric epilepsy</a>”</b></h2> </div> </div><div class="results-container"><div class="chart-block" style="padding:15px;"> <div class="left"> <div id="results" class="results"></div> </div> <div class="right"> <div class="chart-container"><canvas id="publicationChart"></canvas></div> </div> <div class="keywordsdiv"> <div style="text-align:center;"><b>Find publication trends on relevant topics</b> </div> <span class="gp-icon icon-tags"><svg viewBox="0 0 512 512" aria-hidden="true" xmlns="http://www.w3.org/2000/svg" width="1em" height="1em"><path d="M20 39.5c-8.836 0-16 7.163-16 16v176c0 4.243 1.686 8.313 4.687 11.314l224 224c6.248 6.248 16.378 6.248 22.626 0l176-176c6.244-6.244 6.25-16.364.013-22.615l-223.5-224A15.999 15.999 0 00196.5 39.5H20zm56 96c0-13.255 10.745-24 24-24s24 10.745 24 24-10.745 24-24 24-24-10.745-24-24z"></path><path d="M259.515 43.015c4.686-4.687 12.284-4.687 16.97 0l228 228c4.686 4.686 4.686 12.284 0 16.97l-180 180c-4.686 4.687-12.284 4.687-16.97 0-4.686-4.686-4.686-12.284 0-16.97L479.029 279.5 259.515 59.985c-4.686-4.686-4.686-12.284 0-16.97z"></path></svg></span> <span id="keyword-stats"></span> </div> </div></div></div><div class="inside-article"><style> table { margin: 0 0 1.5em; 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if (!statistics || Object.keys(statistics).length === 0) { resultsContainer.innerHTML = '<p>No data found.</p>'; return; } var tableHTML = `<div class='pub-scroll'> <table class='tablediv' border='1' cellspacing='0' cellpadding='0'> <tr> <th>Year</th> <th>Publication Count</th> </tr>`; Object.entries(statistics).sort(([yearA], [yearB]) => yearB - yearA).forEach(([year, count]) => { const displayCount = count === 0 ? 'NA' : count; tableHTML += ` <tr> <td>${year}</td> <td>${displayCount}</td> </tr> `; }); tableHTML += '</table></div>'; resultsContainer.innerHTML = tableHTML; } function displayLineChart(statistics) { var years = Object.keys(statistics); var counts = Object.values(statistics); var ctx = document.getElementById('publicationChart').getContext('2d'); // Destroy existing chart instance if it exists if (chart !== null) { chart.destroy(); } // Create a new chart instance chart = new Chart(ctx, { type: 'line', data: { labels: years, datasets: [{ label: 'Publication Counts', data: counts, fill: false, borderColor: 'rgba(75, 192, 192, 1)', tension: 0.1 }] }, options: { scales: { y: { beginAtZero: true } }, plugins: { legend: { display: true, position: 'top' } } } }); } function displayKeywordStats(keywords) { var resultsContainer = document.getElementById('keyword-stats'); resultsContainer.innerHTML = ''; if (!keywords || keywords.length === 0) { resultsContainer.innerHTML = '<p>No data found.</p>'; return; } var keywordHTML = ''; keywords.forEach((key, index) => { let key_replace = key.replace(/ /g, '-'); key_replace = key_replace.toLowerCase(); keywordHTML += `<a href="https://neonataldisorders.com/publication-trends/index/${key_replace}" target="_blank" title="${key} - yearwise publication trends">${key}</a>`; if (index < keywords.length - 1) { keywordHTML += ', '; } }); resultsContainer.innerHTML = keywordHTML; } // Call the function with the PHP data var statistics = { "2014": 74, "2015": 76, "2016": 111, "2017": 95, "2018": 104, "2019": 175, "2020": 243, "2021": 259, "2022": 386, "2023": 616, "2024": 273 }; var keywordsArray = ["artificial intelligence","epilepsy","epilepsy diagnosis","neurological disorder","neurodegenerative disorder","neurological","paediatric neurologist","epilepsy symptoms","Genetic Testing","Neurostimulation","Data Analytics","Smart Implants"]; displayResults(statistics); displayLineChart(statistics); displayKeywordStats(keywordsArray); </script></p> <p><span style="font-weight: 400;">Certainly, the most novel strategy within this context is the employment of deep convolutional neural networks (CNNs). Such networks can be trained with large data samples of EEG records from children and learn to distinguish between normal and pathological brain signals successfully. For instance, by employing a two-dimensional deep convolutional autoencoder model, it has been possible to achieve significant accuracy of ictal and interictal brain state signals in children for classification. This model enjoys particularly high accuracy rates, thus constituting a benefit to clinicians in the diagnosis of epilepsy that does not require invasive methods. </span></p> <p><span style="font-weight: 400;">However, the use of the machine learning algorithm is not restricted to the analysis of electroencephalogram signals. Some of the recent developments in genetic algorithms and other sets of genetic predictors are now being used to predict epileptic seizures, sometimes before they happen. It ensures that the right interventions are offered to children with epilepsy, reducing the overall quality of life they would otherwise lead. The use of features derived from EEG are often used in various predictive models, and these features include those obtained via a genetic algorithm frequency domain search. Such models have been seen to provide promising results for identifying the preictal state in pediatric cases. </span><span style="font-weight: 400;"> </span></p> <p><span style="font-weight: 400;"> It also applies to elevating the diagnostic process and including these technologies in reference to clinical practices. For example, automated systems with the help of AI can always superpose EEG signals and notify medical personnel of critical situations in real-time. This capability is well required in the intensive care units, where one has to respond promptly to a developing seizure to avoid serious complications. </span></p> <p></div></div> <div style="background: #f7f7f7;border: 1px solid rgba(0, 0, 0, 0.07);"> <div style="padding: 30px;"><div class="Adblock-main"> <div class="Adblock-head"> <h2>Recent Publications on <b>“<a href="https://neonataldisorders.com/recent-publications/index/pediatric epilepsy" target="_blank" rel="noopener" title="pediatric epilepsy - yearwise publication list">pediatric epilepsy</a>”</b></h2> </div> </div> <div class="pb-main"><div class="article-scroll"><div id="results_recent" class="results"></div></div><div class="keywordsdiv" style="margin: 0px 15px;margin-top:20px;"> <div style="text-align:center;"><b>Find publications on relevant topics</b> </div> <span class="gp-icon icon-tags"><svg viewBox="0 0 512 512" aria-hidden="true" xmlns="http://www.w3.org/2000/svg" width="1em" height="1em"><path d="M20 39.5c-8.836 0-16 7.163-16 16v176c0 4.243 1.686 8.313 4.687 11.314l224 224c6.248 6.248 16.378 6.248 22.626 0l176-176c6.244-6.244 6.25-16.364.013-22.615l-223.5-224A15.999 15.999 0 00196.5 39.5H20zm56 96c0-13.255 10.745-24 24-24s24 10.745 24 24-10.745 24-24 24-24-10.745-24-24z"></path><path d="M259.515 43.015c4.686-4.687 12.284-4.687 16.97 0l228 228c4.686 4.686 4.686 12.284 0 16.97l-180 180c-4.686 4.687-12.284 4.687-16.97 0-4.686-4.686-4.686-12.284 0-16.97L479.029 279.5 259.515 59.985c-4.686-4.686-4.686-12.284 0-16.97z"></path></svg></span> <span id="keyword-papers"></span> </div></div></div><div class="inside-article"> <style> .pb-main{ border: solid 1px #ccc; border-top: none; margin-bottom: 20px; padding-bottom: 25px; background:#fff; } .author-main { border: solid 1px #ccc; border-top: none; margin-bottom: 20px; padding-bottom: 25px; background:#fff; } .publication-block { padding: 10px; margin-bottom: 10px; background-color: #f9f9f9; text-align: left; background: #FFF; border-bottom: solid 1px #ccc; margin-left: 15px; margin-right: 15px; } .publication-block h3 { margin: 0 0 10px; color: #000!important; } .publication-block a { font-size: 16px !important; line-height: 1em; font-weight: 600; text-transform: none; color: #000; padding: 0px; } .publication-block a:hover{ color: #227cdc; text-decoration:underline; } .article-scroll { max-height: 445px; overflow-y: auto; overflow-x: hidden; } ::-webkit-scrollbar-track { -webkit-box-shadow: inset 0 0 6px rgba(0,0,0,0.3); background-color: #efefef; border-radius:30px; } ::-webkit-scrollbar { width: 6px; background-color: #efefef; border-radius:30px; } ::-webkit-scrollbar-thumb { background-color: #ababab; border-radius:30px; } .publication-block p { margin-bottom: .5em; font-size: 15px; color: #000; } h3 { font-size: 18px !important; margin-bottom: 20px; line-height: 1.2em; font-weight: 600; text-transform: none; } a { padding: 5px; color: #a71c49; } #keyword-papers{ margin-top: 20px; text-align: center; } </style> <script> function decodeString(str) { str = str.replace(/\\'/g, "'"); str = str.replace(/\\'/g, "'"); str = str.replace(/\\'/g, "'"); return str; } function displayResults_recent(papers) { var resultsContainer = document.getElementById('results_recent'); if (!papers || papers.length === 0) { resultsContainer.innerHTML = '<p>No recent publications found.</p>'; return; } papers.forEach(paper => { var publicationBlock = document.createElement('div'); publicationBlock.className = 'publication-block'; var title_de = decodeString(paper.title); var publicationHTML = ` <div style="margin-bottom: 10px;line-height: 24px;"><a href="${paper.url}" target="_blank" title="${title_de}">${title_de}</a></div> <p><strong>Issue Release:</strong> ${paper.publishedDate}</p> `; publicationBlock.innerHTML = publicationHTML; resultsContainer.appendChild(publicationBlock); }); } function displayKeywordPapers(keywords) { var resultsContainer = document.getElementById('keyword-papers'); resultsContainer.innerHTML = ''; if (!keywords || keywords.length === 0) { resultsContainer.innerHTML = '<p>No data found.</p>'; return; } var keywordHTML = ''; keywords.forEach((key, index) => { let key_replace = key.replace(/ /g, '-'); key_replace = key_replace.toLowerCase(); keywordHTML += `<a href="https://neonataldisorders.com/recent-publications/index/${key_replace}" target="_blank" title="${key} - publication list">${key}</a>`; if (index < keywords.length - 1) { keywordHTML += ', '; } }); resultsContainer.innerHTML = keywordHTML; } // Call the function with the PHP data var recent_papers = [ { "title": "Unusual Voltage-Gated Sodium and Potassium Channelopathies Related to Epilepsy.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38951973", "publishedDate": "2024" }, { "title": "Split intein converting peptide protein interaction into electrochemically assisted metal ion catalytic signal in the prenatal screening of pediatric epilepsy.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38889537", "publishedDate": "2024" }, { "title": "Advances in the study of gut microbes in pediatric epilepsy.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38885595", "publishedDate": "2024" }, { "title": "The Utility of Genetic Testing in Infantile Epileptic Spasms Syndrome: A Step-Based Approach in the Next-Generation Sequencing Era.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38905742", "publishedDate": "2024" }, { "title": "Safety and efficacy of levetiracetam and carbamazepine monotherapy in the management of pediatric focal epilepsy: a randomized clinical trial.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38265679", "publishedDate": "2024" }, { "title": "Radio-pathologic correlation: no pial angioma-subarachnoid varicose network drainage pathway in Sturge-Weber syndrome.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38864886", "publishedDate": "2024" }, { "title": "Risk factors for epilepsy following arterial ischemic stroke childhood: A retrospective cohort study.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38936215", "publishedDate": "2024" }, { "title": "Vagus nerve stimulation in pediatric patients with drug-resistant epilepsy: a step-by-step video.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38957417", "publishedDate": "2024" }, { "title": "A Clinical Neurological Approach to the Child With Adenosine Deaminase Deficiency.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38959649", "publishedDate": "2024" }, { "title": "Minipterional craniotomy for resection of epileptogenic cavernous malformation.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38957416", "publishedDate": "2024" }, { "title": "Escaping the Procrustean Bed: A Perspective on Pediatric Stereoelectroencephalography.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38935654", "publishedDate": "2024" }, { "title": "New Pharmacological Therapies in the Treatment of Epilepsy in the Pediatric Population.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38930098", "publishedDate": "2024" }, { "title": "Microsurgical lesionectomy for drug-resistant insular cortex epilepsy in focal cortical dysplasia type IIB: a pediatric case report.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/39118722", "publishedDate": "2024" }, { "title": "Editors\\\\\\' Note: Comparison of Hemispheric Surgery Techniques for Pediatric Drug-Resistant Epilepsy: An Individual Patient Data Meta-Analysis.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38896814", "publishedDate": "2024" }, { "title": "Any Way You Slice It: Corpus Callosotomy in Pediatric Drug-Resistant Epilepsy.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38898914", "publishedDate": "2024" }, { "title": "Valine and Inflammation Drive Epilepsy in a Mouse Model of ECHS1 Deficiency.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38915588", "publishedDate": "2024" }, { "title": "Building a pediatric neurocritical care program: The role of the clinical pharmacist practitioner on clinical practice and education. A curriculum for neuropharmacology training.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38677803", "publishedDate": "2024" }, { "title": "Delineating abnormal individual structural covariance brain network organization in pediatric epilepsy with unilateral resection of visual cortex.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38826153", "publishedDate": "2024" }, { "title": "Respiratory Syncytial Virus in a Child With Dravet Syndrome: A Case Report.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38826591", "publishedDate": "2024" }, { "title": "A Case of Necrotic Colonic Volvulus in Cerebral Palsy With Severe Scoliosis.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38650790", "publishedDate": "2024" } ]; var keywordsArray = ["artificial intelligence","epilepsy","epilepsy diagnosis","neurological disorder","neurodegenerative disorder","neurological","paediatric neurologist","epilepsy symptoms","Genetic Testing","Neurostimulation","Data Analytics","Smart Implants"]; displayResults_recent(recent_papers); displayKeywordPapers(keywordsArray); // function stripslashes(str) { // if (typeof str === 'string') { // return str.replace(/\/g, ''); // } // } </script></p> <p><span style="font-weight: 400;">Also, wearable technology is changing the way epilepsy is monitored in other settings than hospitals. Presently, users are now able to use wearable devices with EEG sensors for the recording of brain activity without the need for invasive processes. There is not only comfort but also general control and assessment of the patient’s status for protracted periods with such devices. The data obtained can be processed with the help of superior computation algorithms to identify possible precursors of a seizure, which can help to take preventive action. </span><span style="font-weight: 400;"> </span></p> <p><span style="font-weight: 400;">But, despite the recent technological progress in diagnosing pediatric epilepsy, there are peculiarities. Some of the concerns that are still considered even now include the protection of patients’ information, the lack of sufficient large annotated datasets for training AI models, and models of integrating such technologies into the current healthcare systems. Also, there is the question of what potential outcome of such diagnostic tools could persist or become trusted in the long term. </span></p> <p><span style="font-weight: 400;">Nevertheless, focusing on these difficulties, it is necessary to mention that the development of technology opens new perspectives for pediatric epilepsy diagnosis in the future. With the continued development of these technologies, it will be possible to have better diagnosis and, therefore, better management of such children and a better quality of life for children with epilepsy.</span></p> <p></p> <h3><strong>References</strong></h3> <ol> <li>Ghazal, T.M., Al Hamadi, H., Umar Nasir, M., Gollapalli, M., Zubair, M., Adnan Khan, M. and Yeob Yeun, C., 2022. <a href="https://onlinelibrary.wiley.com/doi/full/10.1155/2022/1051388">Supervised machine learning empowered multifactorial genetic inheritance disorder prediction.</a> <i>Computational Intelligence and Neuroscience</i>, <i>2022</i>(1), p.1051388.</li> <li>Natu, M., Bachute, M., Gite, S., Kotecha, K. and Vidyarthi, A., 2022. [<a href="https://onlinelibrary.wiley.com/doi/full/10.1155/2022/7751263">Retracted] Review on Epileptic Seizure Prediction: Machine Learning and Deep Learning Approaches.</a> <i>Computational and Mathematical Methods in Medicine</i>, <i>2022</i>(1), p.7751263.</li> <li>Lekshmy, H.O., Panickar, D. and Harikumar, S., 2022. <a href="https://iopscience.iop.org/article/10.1088/1742-6596/2161/1/012055/meta">Comparative analysis of multiple machine learning algorithms for epileptic seizure prediction.</a> In <i>Journal of physics: Conference series</i> (Vol. 2161, No. 1, p. 012055). IOP Publishing.</li> <li>Nair, P.P., Aghoram, R. and Khilari, M.L., 2021. <a href="https://journals.lww.com/iamr/fulltext/2021/08020/applications_of_artificial_intelligence_in.2.aspx">Applications of artificial intelligence in epilepsy. </a><i>International Journal of Advanced Medical and Health Research</i>, <i>8</i>(2), pp.41-48.</li> <li>Abdelhameed, A. and Bayoumi, M., 2021. <a href="https://www.frontiersin.org/journals/computational-neuroscience/articles/10.3389/fncom.2021.650050/full">A deep learning approach for automatic seizure detection in children with epilepsy.</a> <i>Frontiers in Computational Neuroscience</i>, <i>15</i>, p.650050.</li> <li>Ilakiyaselvan, N., Khan, A.N. and Shahina, A., 2020. <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7324278/">Deep learning approach to detect seizure using reconstructed phase space images.</a> <i>Journal of biomedical research</i>, <i>34</i>(3), p.240.</li> <li>Sharma, P., Hussain, A. and Greenwood, R., 2019. <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6367658/">Precision in pediatric epilepsy.</a> <i>F1000Research</i>, <i>8</i>.</li> <li>Kinney-Lang, E., Yoong, M., Hunter, M., Tallur, K.K., Shetty, J., McLellan, A., Chin, R.F. and Escudero, J., 2019. <a href="https://www.sciencedirect.com/science/article/abs/pii/S1525505018306784">Analysis of EEG networks and their correlation with cognitive impairment in preschool children with epilepsy. </a><i>Epilepsy & Behavior</i>, <i>90</i>, pp.45-56.</li> </ol> <p></div></div> <div style="background: #f7f7f7;border: 1px solid rgba(0, 0, 0, 0.07);"> <div style="padding: 30px;"><div class="Adblock-main"> <div class="Adblock-head"> <h2>Top Experts on “<b style="color:#000;font-size:22px;">pediatric epilepsy</b>“</h2> </div> </div><div class="author-main"><div id="results_author"></div><div style="text-align: center;"><a class="register-button" href="https://neonataldisorders.com/expert-search" target="_blank" rel="noopener">Find experts on any field</a></div></div><div class="inside-article" style="background: none;border: none;box-shadow: none;margin-top: -70px;"> <style> .author-block { padding: 15px; margin-bottom: 10px; text-align: left; font-size: 15px; line-height: 1.2; background: #FFF; border-bottom: solid 1px #ccc; margin-left: 15px; margin-right: 15px; } .author-block h3 { margin: 0 0 10px; color: #227cdc; } .author-block p { margin: 5px 0; } .author-b { display: flex; justify-content: space-between; flex-wrap: wrap; margin-bottom:10px; } .author-b .ainfo { flex: 1 1 30%; box-sizing: border-box; text-align: left; background: #dcdcdc; padding: 7px 14px; border-radius: 5px; margin-top: 3px; margin-right: 10px; } @media (max-width: 768px) { .author-b .ainfo { flex: 1 1 100%; margin: 10px 0; } } </style> <script> function displayResults_author(authors) { var resultsContainer = document.getElementById('results_author'); resultsContainer.innerHTML = ''; if (!authors || Object.keys(authors).length === 0) { resultsContainer.innerHTML = '<p>No authors found.</p>'; return; } Object.values(authors).slice(0, 10).forEach(author => { if (author.affiliation.length > 400) { return; } var authorBlock = document.createElement('div'); authorBlock.className = 'author-block'; var author_name=author.name; let key_replace = author_name.replace(/ /g, '-'); key_replace = key_replace.toLowerCase(); var authorHTML = ` <h3><a href="https://neonataldisorders.com/author/index/${key_replace}\/${author.aid}" target="_blank" title="${author.name}">${author.name}</a></h3> <div class="author-b"> <div class="ainfo"><strong>H-Index:</strong> ${author.hindex}</div> <div class="ainfo"><strong>Publication Count:</strong> ${author.paper_count}</div> <div class="ainfo"><strong>Citation Count:</strong> ${author.citation_count}</div> </div> <p><strong>Affiliation:</strong> ${author.affiliation}</p> `; authorBlock.innerHTML = authorHTML; resultsContainer.appendChild(authorBlock); }); } function displayKeywordAuthors(keywords) { var resultsContainer = document.getElementById('keyword-authors'); resultsContainer.innerHTML = ''; if (!keywords || keywords.length === 0) { resultsContainer.innerHTML = '<p>No data found.</p>'; return; } var keywordHTML = ''; keywords.forEach(key => { let key_replace = key.replace(/ /g, '-'); key_replace = key_replace.toLowerCase(); keywordHTML += `<a href="https://neonataldisorders.com/expert-search/index/${key_replace}" target="_blank" title="${key}">${key}</a>`; }); resultsContainer.innerHTML = keywordHTML; } // Call the function with the PHP data var authors_data = { "z8UpK4wBWBy50K-rVUWM": { "aid": "z8UpK4wBWBy50K-rVUWM", "name": "B. 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", "email": "sheffalig@yahoo.com", "slug_tail": "s-gulati" } }; //console.log(authors_data); displayResults_author(authors_data); var keywordsArray = ["artificial intelligence","epilepsy","epilepsy diagnosis","neurological disorder","neurodegenerative disorder","neurological","paediatric neurologist","epilepsy symptoms","Genetic Testing","Neurostimulation","Data Analytics","Smart Implants"]; displayKeywordAuthors(keywordsArray); </script></p> </div> <footer class="entry-meta" aria-label="Entry meta"> <span class="cat-links"><span class="gp-icon icon-categories"><svg viewBox="0 0 512 512" aria-hidden="true" xmlns="http://www.w3.org/2000/svg" width="1em" height="1em"><path d="M0 112c0-26.51 21.49-48 48-48h110.014a48 48 0 0143.592 27.907l12.349 26.791A16 16 0 00228.486 128H464c26.51 0 48 21.49 48 48v224c0 26.51-21.49 48-48 48H48c-26.51 0-48-21.49-48-48V112z" /></svg></span><span class="screen-reader-text">Categories </span><a 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