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International Conference on Clinical Pathology, Medical Imaging, and Cancer Research (IC-CPMICR)

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Articles

Integrating Artificial Intelligence in Clinical Pathology for Early Detection of Lung Cancer

Dr. Aishwarya Patel, Dr. Karan Mehta, Dr. Rohit Kumar, Dr. Priya Gupta, Dr. Vikram Singh, Dr. John Stevens

Year: 2021 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

The integration of artificial intelligence (AI) in clinical pathology has shown significant promise in enhancing the early detection of lung cancer. This paper presents a framework for utilizing AI-based image analysis tools to identify early-stage lung cancer from CT scans, biopsy slides, and other clinical data. The proposed system focuses on leveraging deep learning models to improve diagnostic accuracy and reduce human error. We evaluated the system's performance using data from multiple hospitals in India and the United States, reporting improved sensitivity and specificity compared to traditional methods. The study also explores the clinical implications and potential for wider adoption in resource-limited settings.

Advancements in Medical Imaging Techniques for Monitoring Breast Cancer Progression

Dr. Ritu Sharma, Dr. Sanjay Patel, Dr. Anjali Verma, Dr. Deepak Bharti, Dr. Sarah Williams

Year: 2021 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

Recent developments in medical imaging technologies, including advanced MRI, PET, and ultrasound, have revolutionized breast cancer monitoring. This research research investigates the comparative efficacy of these imaging techniques in tracking tumor growth, response to therapy, and metastasis. Through a longitudinal study conducted across five Indian hospitals, we demonstrate the potential of dynamic contrast-enhanced MRI to provide superior monitoring for breast cancer patients. Additionally, the integration of machine learning algorithms for automated image analysis has enhanced precision, offering new opportunities for personalized treatment planning. This paper concludes by discussing the clinical utility and challenges in implementing these technologies.

Role of Biomarkers in Improving Early Diagnosis of Ovarian Cancer Through Imaging Modalities

Dr. Meenal Desai, Dr. Sunil Yadav, Dr. Pooja Jain, Dr. Amit Kapoor, Dr. Emily Thomson

Year: 2021 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

Ovarian cancer is often diagnosed at advanced stages, significantly affecting patient outcomes. This paper explores the potential of incorporating novel biomarkers into imaging into imaging techniques like CT scans and ultrasound for early diagnosis. A cohort study of 300 women from India and the UK was conducted to examine the correlation between biomarker levels and imaging findings. The results show that specific biomarkers, when combined with advanced imaging techniques, can detect ovarian cancer at earlier, more treatable stages. This paper highlights the clinical benefits, challenges, and future prospects of this integrated approach.

Exploring the Role of CT Imaging in Evaluating Cancerous Lymph Node Involvement in Head and Neck Tumors

Dr. Amit Sharma, Dr. Neha Gupta, Dr. Rajesh Verma, Dr. Mohammad Ali, Dr. David White

Year: 2021 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

Accurate assessment of lymph node involvement in head and neck cancers is crucial for staging and treatment planning. This research evaluates the effectiveness of of multi-phase CT imaging in detecting metastatic lymph nodes in patients diagnosed with oral cavity, pharyngeal, and laryngeal cancers. Data from over 500 patients in India and the US was analyzed, showing that contrast-enhanced CT scans provide a high sensitivity for detecting lymph node metastasis. Additionally, we discuss the implementation of AI algorithms to predict lymph node involvement, potentially reducing unnecessary invasive procedures and improving patient outcomes.

Machine Learning for Predicting Chemotherapy Response in Colorectal Cancer Patients Based on Imaging Data

Dr. Anupama Rao, Dr. Ravi Patel, Dr. Shweta Iyer, Dr. Harish Kumar, Dr. Olivia Green

Year: 2021 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

The ability to predict chemotherapy response in colorectal cancer (CRC) patients is a key challenge. This study explores the use of machine learning algorithms combined combined with medical imaging to predict treatment outcomes in CRC. We developed a model based on pre-treatment CT and MRI images, patient clinical data, and genetic markers from a cohort of 200 patients in India. The results suggest that our model can accurately predict the likelihood of chemotherapy response, aiding clinicians in making personalized treatment decisions. This study underscores the potential of AI to optimize cancer care by improving treatment response prediction.

Enhancing Accuracy of Prostate Cancer Diagnosis Using Multi-parametric MRI Imaging and Clinical Data Fusion

Dr. Arvind Singh, Dr. Priya Menon, Dr. Raghav Sharma, Dr. Zainab Khan, Dr. Christopher Lee

Year: 2021 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

Prostate cancer diagnosis remains challenging due to the limitations of traditional imaging modalities. This paper examines the use of multi-parametric MRI (mpMRI) in in combination with clinical data to improve diagnostic accuracy. A study of 250 prostate cancer patients from India and the US demonstrated that mpMRI, when integrated with clinical markers, provided a more accurate diagnosis than conventional imaging methods. We discuss how this integrated approach can lead to better clinical decision-making, reduce unnecessary biopsies, and enhance patient outcomes in prostate cancer management.

Evaluating the Efficacy of PET-CT Imaging in Predicting the Recurrence of Lung Cancer Post-Surgery

Dr. Nidhi Sharma, Dr. Shubham Verma, Dr. Jasmeet Kaur, Dr. Ahmed Tariq, Dr. Laura Mitchell

Year: 2021 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

Predicting recurrence of lung cancer post-surgery is critical for patient prognosis. This paper investigates the use of PET-CT imaging for detecting early signs of of recurrence in lung cancer patients after surgical resection. Through a retrospective study of 400 patients from India and the US, we found that PET-CT scans provided superior sensitivity compared to traditional imaging modalities like chest X-rays and CT scans. The study suggests that PET-CT could be integrated into routine post-surgical follow-up, enhancing early detection of recurrence and improving survival rates.

Role of Histopathological Imaging in Differentiating Between Malignant and Benign Melanomas

Dr. Preeti Sood, Dr. Rajiv Bhatt, Dr. Meher Ali, Dr. Akshay Gupta, Dr. Henry Harris

Year: 2021 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

Differentiating malignant from benign melanomas is crucial for determining appropriate treatment strategies. This research explores the role of histopathological imaging, , including digital microscopy and histochemical staining, in making this distinction. Using a dataset of 300 melanoma samples from India and the UK, we evaluate the diagnostic accuracy of these imaging techniques. Our results indicate that digital histopathological imaging, combined with machine learning-based analysis, significantly improves diagnostic accuracy, enabling pathologists to make more precise assessments and thereby reducing misdiagnosis rates.

Investigating the Correlation Between Tumor Vascularity and Prognosis in Brain Cancer Using MRI Angiography

Dr. Tanvi Singh, Dr. Nikhil Deshmukh, Dr. Rohit Tiwari, Dr. Elsa Johansson, Dr. Brian Lee

Year: 2021 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

Tumor vascularity is a key factor in determining the aggressiveness and prognosis of brain cancer. This study uses MRI angiography to assess the relationship between tumor tumor vascularity and patient prognosis in glioblastoma and other brain tumors. A cohort of 150 patients from India and Sweden was analyzed, revealing a strong correlation between increased tumor vascularity and poor prognosis. This research underscores the potential of MRI angiography as a non-invasive tool for predicting patient outcomes, offering a complementary approach to traditional histopathological techniques.

Digital Pathology and Imaging-Based Assessment for Early Detection of Cervical Cancer

Dr. Sunita Reddy, Dr. Harpreet Kaur, Dr. Vikas Yadav, Dr. Jessica Clark, Dr. Peter Walker

Year: 2021 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

Early detection of cervical cancer remains a critical challenge in reducing mortality rates. This paper explores the role of digital pathology and imaging-based assessments assessments in improving early detection rates. By analyzing data from over 200 women in India, we show that integrating digital histopathology with cervical imaging modalities such as colposcopy and HPV testing significantly enhances early detection. Additionally, the application of AI-driven diagnostic algorithms helps identify high-risk patients for further investigation. The results suggest that this integrated approach could be a game-changer in cervical cancer screening programs.


International Conference on Sustainable Energy and Materials Engineering (ICSEME)

International Conference on Biomedical Robotics and Computational Imaging (ICBRCI)

International Conference on Smart Cities and Civil Infrastructure (ICSCCI)

International Conference on Aerospace Technologies and Data Science (ICATDS)

International Conference on Renewable Resources and Chemical Engineering (ICRRCE)

International Conference on Cyber-Physical Systems and Electrical Engineering (ICCPSE)

International Conference on Robotics in Manufacturing and Environmental Engineering (ICRMEE)

International Conference on Advanced Materials and Mechanical Engineering (ICAMME)

International Conference on Nanotechnology for Electrical Systems (ICNES)

International Conference on Geotechnical Innovations and Computer-Aided Design (ICGICAD)

International Conference on Water Resources and Environmental Engineering (ICWREE)

International Conference on Intelligent Transportation Systems and Structural Engineering (ICITSE)

International Conference on Sustainable Energy and Materials Engineering (ICSEME)

International Conference on Biomedical Robotics and Computational Imaging (ICBRCI)

International Conference on Smart Cities and Civil Infrastructure (ICSCCI)

International Conference on Aerospace Technologies and Data Science (ICATDS)

International Conference on Renewable Resources and Chemical Engineering (ICRRCE)

International Conference on Cyber-Physical Systems and Electrical Engineering (ICCPSE)

International Conference on Robotics in Manufacturing and Environmental Engineering (ICRMEE)

International Conference on Advanced Materials and Mechanical Engineering (ICAMME)

International Conference on Nanotechnology for Electrical Systems (ICNES)

International Conference on Geotechnical Innovations and Computer-Aided Design (ICGICAD)

International Conference on Water Resources and Environmental Engineering (ICWREE)

International Conference on Intelligent Transportation Systems and Structural Engineering (ICITSE)

International Conference on Sustainable Energy and Materials Engineering (ICSEME)

International Conference on Biomedical Robotics and Computational Imaging (ICBRCI)

International Conference on Smart Cities and Civil Infrastructure (ICSCCI)

International Conference on Aerospace Technologies and Data Science (ICATDS)

International Conference on Renewable Resources and Chemical Engineering (ICRRCE)

International Conference on Cyber-Physical Systems and Electrical Engineering (ICCPSE)

International Conference on Robotics in Manufacturing and Environmental Engineering (ICRMEE)

International Conference on Advanced Materials and Mechanical Engineering (ICAMME)

International Conference on Nanotechnology for Electrical Systems (ICNES)

International Conference on Geotechnical Innovations and Computer-Aided Design (ICGICAD)

International Conference on Water Resources and Environmental Engineering (ICWREE)

International Conference on Intelligent Transportation Systems and Structural Engineering (ICITSE)

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