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EDITORIAL
Yash Pradeep Vaidya, Sara Jane Shumway
BACKGROUND: Artificial intelligence (AI) is a rapidly emerging field of computer science with a significant predicted impact in cardiothoracic surgery. We investigate the role of this tool in the preoperative planning, intraoperative assistance, and postoperative management of patients. We also describe the future applications in the field and provide an insight on the advancements we have made at our institution. METHODS: We assessed the literature in the Medline and Google Scholar databases that describe the use of artificial intelligence in thoracic, congenital, and adult cardiac surgery...
April 27, 2024: Journal of Thoracic and Cardiovascular Surgery
#22
JOURNAL ARTICLE
Sarah L Stenton, Melanie C O'Leary, Gabrielle Lemire, Grace E VanNoy, Stephanie DiTroia, Vijay S Ganesh, Emily Groopman, Emily O'Heir, Brian Mangilog, Ikeoluwa Osei-Owusu, Lynn S Pais, Jillian Serrano, Moriel Singer-Berk, Ben Weisburd, Michael W Wilson, Christina Austin-Tse, Marwa Abdelhakim, Azza Althagafi, Giulia Babbi, Riccardo Bellazzi, Samuele Bovo, Maria Giulia Carta, Rita Casadio, Pieter-Jan Coenen, Federica De Paoli, Matteo Floris, Manavalan Gajapathy, Robert Hoehndorf, Julius O B Jacobsen, Thomas Joseph, Akash Kamandula, Panagiotis Katsonis, Cyrielle Kint, Olivier Lichtarge, Ivan Limongelli, Yulan Lu, Paolo Magni, Tarun Karthik Kumar Mamidi, Pier Luigi Martelli, Marta Mulargia, Giovanna Nicora, Keith Nykamp, Vikas Pejaver, Yisu Peng, Thi Hong Cam Pham, Maurizio S Podda, Aditya Rao, Ettore Rizzo, Vangala G Saipradeep, Castrense Savojardo, Peter Schols, Yang Shen, Naveen Sivadasan, Damian Smedley, Dorian Soru, Rajgopal Srinivasan, Yuanfei Sun, Uma Sunderam, Wuwei Tan, Naina Tiwari, Xiao Wang, Yaqiong Wang, Amanda Williams, Elizabeth A Worthey, Rujie Yin, Yuning You, Daniel Zeiberg, Susanna Zucca, Constantina Bakolitsa, Steven E Brenner, Stephanie M Fullerton, Predrag Radivojac, Heidi L Rehm, Anne O'Donnell-Luria
BACKGROUND: A major obstacle faced by families with rare diseases is obtaining a genetic diagnosis. The average "diagnostic odyssey" lasts over five years and causal variants are identified in under 50%, even when capturing variants genome-wide. To aid in the interpretation and prioritization of the vast number of variants detected, computational methods are proliferating. Knowing which tools are most effective remains unclear. To evaluate the performance of computational methods, and to encourage innovation in method development, we designed a Critical Assessment of Genome Interpretation (CAGI) community challenge to place variant prioritization models head-to-head in a real-life clinical diagnostic setting...
April 29, 2024: Human Genomics
#23
JOURNAL ARTICLE
Zhihong Chen, Lisha Yao, Yue Liu, Xiaorui Han, Zhengze Gong, Jichao Luo, Jietong Zhao, Gang Fang
Accurate multi-organ segmentation in 3D CT images is imperative for enhancing computer-aided diagnosis and radiotherapy planning. However, current deep learning-based methods for 3D multi-organ segmentation face challenges such as the need for labor-intensive manual pixel-level annotations and high hardware resource demands, especially regarding GPU resources. To address these issues, we propose a 3D proxy-bridged region-growing framework specifically designed for the segmentation of the liver and spleen...
April 29, 2024: Scientific Reports
#24
JOURNAL ARTICLE
Jie Chen, Huilian Zhang, Quan Zou, Bo Liao, Xia-An Bi
Autism spectrum disorder (ASD) is a complex, severe disorder related to brain development. It impairs patient language communication and social behaviors. In recent years, ASD researches have focused on a single-modal neuroimaging data, neglecting the complementarity between multi-modal data. This omission may lead to poor classification. Therefore, it is important to study multi-modal data of ASD for revealing its pathogenesis. Furthermore, recurrent neural network (RNN) and gated recurrent unit (GRU) are effective for sequence data processing...
April 29, 2024: Interdisciplinary Sciences, Computational Life Sciences
#25
JOURNAL ARTICLE
Manisha Koneru, Hamza A Shaikh, Daniel A Tonetti, James E Siegler, Jane Khalife, Ajith J Thomas, Tudor G Jovin, Corey M Mossop
Objective Identifying ischemic stroke is a diagnostic challenge in the trauma subpopulation. We describe our early experience with artificial intelligence-assisted image analysis software for automatically identifying acute ischemic stroke in trauma patients. Methods Patients were retrospectively screened for (i) admission to the trauma service at a level one trauma center between 2020 and 2022, (ii) radiologist-confirmed intracranial occlusion, (iii) occlusion identified on computed tomography angiography performed within 24 hours of admission, (iv) no intracranial hemorrhage, and (v) contemporaneous analysis with the large vessel occlusion (LVO) detection program...
March 2024: Curēus
#26
REVIEW
Mahi Basra, Hemangi Patel, Alexandria Sobczak, Jordan Ditchek, Alejandro Biglione, Marc M Kesselman, Alessandra Posey
Spondyloarthropathy (SpA) is one of the most common causes of low back pain. It is caused by inflammatory arthritis in the spine, manifesting in various forms such as psoriatic arthritis (PsA), ankylosing spondylitis (AS), and sacroiliitis. A comprehensive systematic literature search was done to evaluate and compare MRI, CT, single-photon emission CT, PET, ultrasound (US) imaging, low-dose CT, and diffusion-weighted imaging (DWI) techniques in assessing SpAs. The search strategy was constructed by an analysis of key terms from relevant articles in MEDLINE ProQuest, Embase, and PubMed...
March 2024: Curēus
#27
Akhileshwar R Ginnaram, Shruti Kumar, Heta B Ladumor, Shilpa Mohanan, Janice W Murphy
Dietrich's disease, also known as Mauclaire's disease, is a rare condition characterized by avascular necrosis of the metacarpal heads, predominantly affecting adolescents. This case report aims to elucidate the diagnostic process and management of Dietrich's disease in adolescents. A 15-year-old male adolescent presented with left ring finger metacarpophalangeal joint pain and restricted range of motion following a remote history of sports-related trauma. Clinical examination revealed tenderness and limited flexion at the affected joint...
March 2024: Curēus
#28
Hardita P Yudhanto, Widiana Ferriastuti, Suresh K Mukherji
Intracranial epidermoid cysts are benign, slow-growing congenital tumors of ectodermal origin. They are rare embryonal benign cystic masses with an incidence rate of approximately 0.04%-0.6% of intracranial tumors. Computed tomography (CT) and magnetic resonance imaging (MRI) are fundamental diagnostic tools providing valuable information for surgical management. We reported a 59-year-old male patient with right limb weakness twelve hours prior to admission, slurred speech, and paresis of the facial nerve. Based on history taking, physical examination, and radiology examinations, we concluded a diagnosis of non-communicated hydrocephalus due to a right cerebellar intra-axial tumor with a suspicion of low-grade glioma (Pylocitic Astrocytoma)...
July 2024: Radiology Case Reports
#29
JOURNAL ARTICLE
Asim Zaman, Haseeb Hassan, Xueqiang Zeng, Rashid Khan, Jiaxi Lu, Huihui Yang, Xiaoqiang Miao, Anbo Cao, Yingjian Yang, Bingding Huang, Yingwei Guo, Yan Kang
INTRODUCTION: In neurological diagnostics, accurate detection and segmentation of brain lesions is crucial. Identifying these lesions is challenging due to its complex morphology, especially when using traditional methods. Conventional methods are either computationally demanding with a marginal impact/enhancement or sacrifice fine details for computational efficiency. Therefore, balancing performance and precision in compute-intensive medical imaging remains a hot research topic. METHODS: We introduce a novel encoder-decoder network architecture named the Adaptive Feature Medical Segmentation Network (AFMS-Net) with two encoder variants: the Single Adaptive Encoder Block (SAEB) and the Dual Adaptive Encoder Block (DAEB)...
2024: Frontiers in Neuroscience
#30
JOURNAL ARTICLE
Zhengye Wang, Miao Wu, Qian Liu, Xiaorong Wang, Chuanbo Yan, Tao Song
UNLABELLED: To properly treat and care for hepatic cystic echinococcosis (HCE), it is essential to make an accurate diagnosis before treatment. OBJECTIVE: The objective of this study was to assess the diagnostic accuracy of computer-aided diagnosis techniques in classifying HCE ultrasound images into five subtypes. METHODS: A total of 1820 HCE ultrasound images collected from 967 patients were included in the study. A multi-kernel learning method was developed to learn the texture and depth features of the ultrasound images...
April 27, 2024: Ultrasound in Medicine & Biology
#31
JOURNAL ARTICLE
Arshia Eskandari, Mahkame Sharbatdar
The tendency of skin diseases to manifest in a unique and yet similar appearance, absence of enough competent dermatologists, and urgency of diagnosis and classification on time and accurately, makes the need of machine aided diagnosis blatant. This study is conducted with the purpose of broadening the research in skin disease diagnosis with computer by traversing the capabilities of deep Learning algorithms to classify two skin diseases noticeably close in appearance, Psoriasis and Lichen Planus. The resemblance between these two skin diseases is striking, often resulting in their classification within the same category...
April 27, 2024: Scientific Reports
#32
JOURNAL ARTICLE
Zhongmiao Huang, Liejun Wang, Lianghui Xu
Medical image segmentation is a key task in computer aided diagnosis. In recent years, convolutional neural network (CNN) has made some achievements in medical image segmentation. However, the convolution operation can only extract features in a fixed size region at a time, which leads to the loss of some key features. The recently popular Transformer has global modeling capabilities, but it does not pay enough attention to local information and cannot accurately segment the edge details of the target area...
April 27, 2024: Scientific Reports
#33
JOURNAL ARTICLE
Wenyuan Shang, Xiujun Hu, Xiaoman Lin, Shangru Li, Shuchang Xiong, Bingding Huang, Xin Wang
Nanobodies (Nbs or VHHs) are single-domain antibodies (sdAbs) derived from camelid heavy-chain antibodies. Nbs have special and unique characteristics, such as small size, good tissue penetration, and cost-effective production, making Nbs a good candidate for the diagnosis and treatment of viruses and other pathologies. Identifying effective Nbs against COVID-19 would help us control this dangerous virus or other unknown variants in the future. Herein, we introduce an in silico screening strategy for optimizing stable conformation of anti-SARS-CoV-2 Nbs...
March 27, 2024: Pharmaceuticals
#34
REVIEW
Jiabao Tian, Xinyu Bai, Camelia Quek
Cancer comprises malignant cells surrounded by the tumor microenvironment (TME), a dynamic ecosystem composed of heterogeneous cell populations that exert unique influences on tumor development. The immune community within the TME plays a substantial role in tumorigenesis and tumor evolution. The innate and adaptive immune cells "talk" to the tumor through ligand-receptor interactions and signaling molecules, forming a complex communication network to influence the cellular and molecular basis of cancer. Such intricate intratumoral immune composition and interactions foster the application of immunotherapies, which empower the immune system against cancer to elicit durable long-term responses in cancer patients...
April 19, 2024: International Journal of Molecular Sciences
#35
JOURNAL ARTICLE
Alaa Shafie, Amal Adnan Ashour, Farah Anjum, Anas Shamsi, Md Imtaiyaz Hassan
Huntington's disease (HD) is a chronic, inherited neurodegenerative condition marked by chorea, dementia, and changes in personality. The primary cause of HD is a mutation characterized by the expansion of a triplet repeat (CAG) within the huntingtin gene located on chromosome 4. Despite substantial progress in elucidating the molecular and cellular mechanisms of HD, an effective treatment for this disorder is not available so far. In recent years, researchers have been interested in studying cerebrospinal fluid (CSF) as a source of biomarkers that could aid in the diagnosis and therapeutic development of this disorder...
April 1, 2024: Journal of Personalized Medicine
#36
JOURNAL ARTICLE
Raj Ponnusamy, Ming Zhang, Yue Wang, Xinyue Sun, Mohammad Chowdhury, Jeffrey B Driban, Timothy McAlindon, Juan Shan
Bone marrow lesion (BML) volume is a potential biomarker of knee osteoarthritis (KOA) as it is associated with cartilage degeneration and pain. However, segmenting and quantifying the BML volume is challenging due to the small size, low contrast, and various positions where the BML may occur. It is also time-consuming to delineate BMLs manually. In this paper, we proposed a fully automatic segmentation method for BMLs without requiring human intervention. The model takes intermediate weighted fat-suppressed (IWFS) magnetic resonance (MR) images as input, and the output BML masks are evaluated using both regular 2D Dice similarity coefficient (DSC) of the slice-level area metric and 3D DSC of the subject-level volume metric...
April 12, 2024: Bioengineering
#37
JOURNAL ARTICLE
Oscar Hernandez Dominguez, Eddy P Lincango, Rebecca Spivak, Federico Almonacid-Cardenas, Christopher Prien, Tairin Uchino, Anna Spivak, Tracy L Hull, Scott R Steele, Stefan D Holubar
BACKGROUND: A colosplenic fistula (CsF) is an extremely rare complication. Its diagnosis and management remain poorly understood, owing to its infrequent incidence. Our objective was to systematically review the etiology, clinical features, diagnosis, management, and prognosis to help clinicians gain a better understanding of this unusual complication and provide aid if it is to be encountered. METHODS: A systematic review of studies reporting CsF diagnosis in Ovid MEDLINE, Ovid EMBASE, Scopus, Web of Science, and Wiley Cochrane Library from 1946 to June 2022...
April 1, 2024: International Journal of Surgery
#38
JOURNAL ARTICLE
Quoc Tuan Hoang, Xuan Hien Pham, Xuan Thang Trinh, Anh Vu Le, Minh V Bui, Trung Thanh Bui
Intracranial hemorrhage (ICH) resulting from traumatic brain injury is a serious issue, often leading to death or long-term disability if not promptly diagnosed. Currently, doctors primarily use Computerized Tomography (CT) scans to detect and precisely locate a hemorrhage, typically interpreted by radiologists. However, this diagnostic process heavily relies on the expertise of medical professionals. To address potential errors, computer-aided diagnosis systems have been developed. In this study, we propose a new method that enhances the localization and segmentation of ICH lesions in CT scans by using multiple images created through different data augmentation techniques...
March 25, 2024: Journal of Imaging
#39
Alaa Safia, Rabie Shehadeh, Shlomo Merchavy
This case report presents a unique and challenging scenario involving the diagnosis and management of a sublingual dermoid cyst in a 12-year-old male with autism disorder. Dermoid cysts within the oral cavity are exceptionally rare entities, constituting less than 0.01% of all oral cavity cysts. In addition, their co-occurrence with neurocognitive disorders further complicates the diagnostic process. The patient's clinical presentation was marked by recurrent epistaxis and behavioral changes, which were compounded by his communication limitations due to autism disorder...
2024: Case Reports in Pediatrics
#40
REVIEW
Sahem Al Muhaisen, Omar Safi, Ahmad Ulayan, Sara Aljawamis, Maryam Fakhoury, Haneen Baydoun, Dua Abuquteish
Worldwide, breast cancer (BC) is one of the most commonly diagnosed malignancies in women. Early detection is key to improving survival rates and health outcomes. This literature review focuses on how artificial intelligence (AI), especially deep learning (DL), can enhance the ability of mammography, a key tool in BC detection, to yield more accurate results. Artificial intelligence has shown promise in reducing diagnostic errors and increasing early cancer detection chances. Nevertheless, significant challenges exist, including the requirement for large amounts of high-quality data and concerns over data privacy...
March 2024: Curēus
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