Amit Nandan Dhar Dwivedi, Nidhi Yadav, Vandana Yadav
Disorders of sexual development (DSD), apart from medical disease, is a psychosocial stigma to not only the patient but also their whole family. We present the case of a 24-year-old 46XX, raised as male, with ambiguous genitalia and cyclical hematuria with normal female internal genitalia and secondary sexual characteristics. This case underscores the influence of social stigma and the psychosocial vulnerability associated with DSD on individuals’ lives in developing countries.
{"title":"The prevailing social stigma around disorders of sexual development in developing countries","authors":"Amit Nandan Dhar Dwivedi, Nidhi Yadav, Vandana Yadav","doi":"10.25259/fh_3_2024","DOIUrl":"https://doi.org/10.25259/fh_3_2024","url":null,"abstract":"Disorders of sexual development (DSD), apart from medical disease, is a psychosocial stigma to not only the patient but also their whole family. We present the case of a 24-year-old 46XX, raised as male, with ambiguous genitalia and cyclical hematuria with normal female internal genitalia and secondary sexual characteristics. This case underscores the influence of social stigma and the psychosocial vulnerability associated with DSD on individuals’ lives in developing countries.","PeriodicalId":517984,"journal":{"name":"Future Health","volume":"18 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140285850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Generative AI is an expanding domain that employs machine learning models to generate novel data that closely mimic pre existing data. ChatGPT and DALL-E can be customized for specific applications and are expected to transform healthcare, education, and communication. Generative Adversarial Networks (GANs) that can generate synthetic medical images closely mimicking actual patient data may substantially enhance machine learning model training datasets. They also translate medical images from one modality to another, improve medical imaging resolution, reduce radiation exposure, and boost image quality and detail. Despite their challenges, GANs have great potential in the field of medical imaging. The key obstacles are the need for Graphic Processing Units (GPUs) and computing resources to train GANs and the lack of established standards for generating synthetic images. Incorrectly labeled data for training other machine learning models can reduce performance, making ground-truth data labeling for healthcare AI more difficult. Generative AI is revolutionizing healthcare imaging, simplifying diagnosis, and propelling healthcare research and practice to new frontiers. Ensuring the reliability and safety of generated images in medical applications requires addressing ethical considerations and validating data.
{"title":"Harnessing generative AI: Transformative applications in medical imaging and beyond","authors":"Swati Goyal, L. Kaushal","doi":"10.25259/fh_12_2024","DOIUrl":"https://doi.org/10.25259/fh_12_2024","url":null,"abstract":"Generative AI is an expanding domain that employs machine learning models to generate novel data that closely mimic pre existing data. ChatGPT and DALL-E can be customized for specific applications and are expected to transform healthcare, education, and communication. Generative Adversarial Networks (GANs) that can generate synthetic medical images closely mimicking actual patient data may substantially enhance machine learning model training datasets. They also translate medical images from one modality to another, improve medical imaging resolution, reduce radiation exposure, and boost image quality and detail.\u0000Despite their challenges, GANs have great potential in the field of medical imaging. The key obstacles are the need for Graphic Processing Units (GPUs) and computing resources to train GANs and the lack of established standards for generating synthetic images. Incorrectly labeled data for training other machine learning models can reduce performance, making ground-truth data labeling for healthcare AI more difficult.\u0000Generative AI is revolutionizing healthcare imaging, simplifying diagnosis, and propelling healthcare research and practice to new frontiers. Ensuring the reliability and safety of generated images in medical applications requires addressing ethical considerations and validating data.","PeriodicalId":517984,"journal":{"name":"Future Health","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140398141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Primary tumors of the omentum are one of the rare causes of large intra-abdominal masses and contribute to a limited number of reported cases in the medical literature. Here, we report a case of a male child with complaints of dull abdominal pain, suspected to be a giant omental lipoma radiologically, which was confirmed on histopathology after a complete surgical resection. The case highlights the importance of various radiological modalities for the diagnosis of omental lipomas and their importance in pre-operative workup to rule out malignant pathologies, and for better anatomical characterization of the lesion for assistance in surgical planning.
{"title":"A curious case of giant omental lipoma","authors":"Prachi Shukla, Farhana Hasan","doi":"10.25259/fh_9_2024","DOIUrl":"https://doi.org/10.25259/fh_9_2024","url":null,"abstract":"Primary tumors of the omentum are one of the rare causes of large intra-abdominal masses and contribute to a limited number of reported cases in the medical literature. Here, we report a case of a male child with complaints of dull abdominal pain, suspected to be a giant omental lipoma radiologically, which was confirmed on histopathology after a complete surgical resection. The case highlights the importance of various radiological modalities for the diagnosis of omental lipomas and their importance in pre-operative workup to rule out malignant pathologies, and for better anatomical characterization of the lesion for assistance in surgical planning.","PeriodicalId":517984,"journal":{"name":"Future Health","volume":"19 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140398130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Double aortic arch (DAA) is a rare cause of esophageal compression. We present a case of a seven-month-old male infant who presented with complaints of dysphagia and wheezing during crying. Computed tomography angiography (CTA) revealed a co-dominant double aortic arch forming a complete vascular ring around the trachea, causing its mild compression. Posteriorly, the aortic arch was seen, causing severe compression of the esophagus. The patient underwent double aortic arch repair and had an uneventful post-operative course, with resolution of the dysphagia.
{"title":"Double aortic arch: A rare case of dysphagia","authors":"Archit Dikshit, Samir Patel, Milin Garachh, Dinesh Patel, Saurabh Deshpande","doi":"10.25259/fh_8_2024","DOIUrl":"https://doi.org/10.25259/fh_8_2024","url":null,"abstract":"Double aortic arch (DAA) is a rare cause of esophageal compression. We present a case of a seven-month-old male infant who presented with complaints of dysphagia and wheezing during crying. Computed tomography angiography (CTA) revealed a co-dominant double aortic arch forming a complete vascular ring around the trachea, causing its mild compression. Posteriorly, the aortic arch was seen, causing severe compression of the esophagus. The patient underwent double aortic arch repair and had an uneventful post-operative course, with resolution of the dysphagia.","PeriodicalId":517984,"journal":{"name":"Future Health","volume":"105 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140286129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Azygous anterior cerebral artery (AACA) is a rare anatomical variant and its occlusion may cause bifrontal infarct with variable neurological deficit and clinical presentation. In our case AACA thrombotic occlusion caused bifrontal infarcts leading to abnormal behavior. Early imaging with CT angiography or MRI with MRA is the key for early diagnosis and prompt management.
{"title":"Azygous anterior cerebral artery thrombosis causing bifrontal infarcts with abnormal behavior","authors":"Amit Kumar Paliwal, Avinash Mishra","doi":"10.25259/fh_2_2024","DOIUrl":"https://doi.org/10.25259/fh_2_2024","url":null,"abstract":"Azygous anterior cerebral artery (AACA) is a rare anatomical variant and its occlusion may cause bifrontal infarct with variable neurological deficit and clinical presentation. In our case AACA thrombotic occlusion caused bifrontal infarcts leading to abnormal behavior. Early imaging with CT angiography or MRI with MRA is the key for early diagnosis and prompt management.","PeriodicalId":517984,"journal":{"name":"Future Health","volume":"67 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140398308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fetus in fetu is a rare disorder with a reported incidence of 1 in 500,000 live births, with only 78 cases reported so far. The most common presentation is abdominal mass in a newborn or infant; however, presentation in later life is also possible. Early detection is by ultrasonography. Computerized tomography is rarely used. However, computerized tomography gives an excellent overview of anatomical information and its exact relation with the surrounding viscera. The present case series is an attempt to highlight the role of cross-sectional imaging in the pre- and post-operative management of this rare disorder.
{"title":"Multidetector computerized tomography in diagnosis and preoperative workup of fetus in fetu: A case series","authors":"Amit Nandan Dhar Dwivedi, Prashant Nath Gupta","doi":"10.25259/fh_1_2024","DOIUrl":"https://doi.org/10.25259/fh_1_2024","url":null,"abstract":"Fetus in fetu is a rare disorder with a reported incidence of 1 in 500,000 live births, with only 78 cases reported so far. The most common presentation is abdominal mass in a newborn or infant; however, presentation in later life is also possible. Early detection is by ultrasonography. Computerized tomography is rarely used. However, computerized tomography gives an excellent overview of anatomical information and its exact relation with the surrounding viscera. The present case series is an attempt to highlight the role of cross-sectional imaging in the pre- and post-operative management of this rare disorder.","PeriodicalId":517984,"journal":{"name":"Future Health","volume":"73 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140286145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article intends to assess how artificial intelligence (AI) affects the automation of X-ray radiography image processing. The field of medical imaging has seen considerable potential in the use of AI algorithms to improve diagnostic precision, streamline procedures, and streamline workflow. The paper explores how AI is currently being used to automate image processing for X-ray radiography, outlining its possible benefits, difficulties, and hopes for the future. According to the results, AI has the potential to revolutionize radiography by helping radiologists evaluate images, locate anomalies, and do quantitative analysis. This discovery may result in important improvements in healthcare. To determine the clinical value and safety of AI-driven solutions, it is necessary to carry out more research and validation. In conclusion, this analysis highlights AI’s critical role in automating image processing for X-ray radiography and demonstrates how it has the potential to completely transform the industry. To guarantee the dependability and efficacy of AI-based techniques in clinical practice, however, continual research and validation are crucial.
本文旨在评估人工智能（AI）如何影响 X 射线放射图像处理的自动化。医学影像领域在使用人工智能算法提高诊断精度、简化程序和简化工作流程方面已经看到了相当大的潜力。本文探讨了目前如何将人工智能用于 X 射线放射影像处理自动化，概述了其可能带来的好处、困难和对未来的希望。研究结果表明，人工智能有可能通过帮助放射科医生评估图像、定位异常和进行定量分析来彻底改变放射学。这一发现可能会给医疗保健带来重大改进。为了确定人工智能驱动解决方案的临床价值和安全性，有必要开展更多的研究和验证。总之，本分析报告强调了人工智能在 X 射线放射影像处理自动化方面的关键作用，并展示了人工智能如何具有彻底改变该行业的潜力。然而，要保证基于人工智能的技术在临床实践中的可靠性和有效性，持续的研究和验证至关重要。
{"title":"Evaluating the role of artificial intelligence in automated image analysis for x-ray radiography","authors":"Dheeraj Kumar, Shailendra Kumar Diwakar, Shubham Gupta","doi":"10.25259/fh_14_2024","DOIUrl":"https://doi.org/10.25259/fh_14_2024","url":null,"abstract":"This article intends to assess how artificial intelligence (AI) affects the automation of X-ray radiography image processing. The field of medical imaging has seen considerable potential in the use of AI algorithms to improve diagnostic precision, streamline procedures, and streamline workflow. The paper explores how AI is currently being used to automate image processing for X-ray radiography, outlining its possible benefits, difficulties, and hopes for the future. According to the results, AI has the potential to revolutionize radiography by helping radiologists evaluate images, locate anomalies, and do quantitative analysis. This discovery may result in important improvements in healthcare. To determine the clinical value and safety of AI-driven solutions, it is necessary to carry out more research and validation. In conclusion, this analysis highlights AI’s critical role in automating image processing for X-ray radiography and demonstrates how it has the potential to completely transform the industry. To guarantee the dependability and efficacy of AI-based techniques in clinical practice, however, continual research and validation are crucial.","PeriodicalId":517984,"journal":{"name":"Future Health","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140398005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We describe three cases of patients with atypical Parkinsonian syndrome (APS), who presented with gait disturbance, postural instability, decreasing facial expression, dyskinesia, and subjective cognitive impairment. The patients underwent magnetic resonance imaging (MRI) Brain for differential diagnosis of APS. MRI made it possible to offer a suggestive diagnosis and determine individual strategic management for patients with APS.
{"title":"Role of MRI in diagnosis of atypical Parkinsonian syndrome: A case series with brief review of literature","authors":"Yada Varun Tej, Harsha Surana, Meenakshi Ahuja, Abhinav C Bhagat, Jitendra Sharma","doi":"10.25259/fh_5_2024","DOIUrl":"https://doi.org/10.25259/fh_5_2024","url":null,"abstract":"We describe three cases of patients with atypical Parkinsonian syndrome (APS), who presented with gait disturbance, postural instability, decreasing facial expression, dyskinesia, and subjective cognitive impairment. The patients underwent magnetic resonance imaging (MRI) Brain for differential diagnosis of APS. MRI made it possible to offer a suggestive diagnosis and determine individual strategic management for patients with APS.","PeriodicalId":517984,"journal":{"name":"Future Health","volume":"5 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140398610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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