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Machine Interaction-Based Computational Tools in Cancer Imaging
Published in Nishu Gupta, Srinivas Kiran Gottapu, Rakesh Nayak, Anil Kumar Gupta, Mohammad Derawi, Jayden Khakurel, Human-Machine Interaction and IoT Applications for a Smarter World, 2023
Praveen Kumar Gupta, Anushree Vinayak Lokur, Shweta Sudam Kallapur, Ryna Shireen Sheriff, A. H. Manjunatha Reddy, V. Chayapathy, Rajendran Sindhu, E. Keshamma
Health sector using computational tools involves the usage of the tools of artificial intelligence (AI), advanced robotics, machine learning, and natural language processing, for the substitution of human expertise. AI in healthcare is a growing field due to the availability of advanced predictive techniques and randomized methods. Discriminative Gaussian processed models are tested on the human face recognition data from various sources in the future; they may be used to detect the image-based pattern recognition. Trunk branch holistic ensemble convolutional neural network has data with both face recognition and video processing. Convolution neural network (CNN) is trained with large amounts of clinical data images that aid in the detection of skin lesions. Using this information for the detection of skin cancer, computer-aided diagnostics (CAD) has rapidly entered radiology mainstream and is used as a second opinion for breast cancer identification. The algorithm has steps for image processing and image feature analysis. This algorithm helps in reducing the improper representation of temporary images that are used as nonconventional images and they are compared for matching the reference image to the current one that is developed. Figure 10.1 shows how the imaging of the bone cancer happens by temporal subtraction method [1].
Lung Tumor Segmentation Using a 3D Densely Connected Convolutional Neural Network
Published in Mohan Lal Kolhe, Kailash J. Karande, Sampat G. Deshmukh, Artificial Intelligence, Internet of Things (IoT) and Smart Materials for Energy Applications, 2023
Shweta Tyagi, Sanjay N. Talbar
For diagnosis of a disease or an injury, there are several medical imaging techniques like X-rays, magnetic resonance imaging (MRI), computed tomography (CT) imaging, positron emission tomography (PET) imaging, sonography, mammography and so on. For patients having lung cancer, the diagnosis is usually done by using three medical imaging tests, X-ray images, CT scans and PET scans, out of which CT scan is preferred because this is more reliable as compared to the chest X-ray images in predicting the nature of the tumor, and it can provide more information about certain lung tumor features, including its size, shape and internal density. The CT scan is examined by the radiologists to detect the tumor region in the lungs. But this process is very time-consuming because one CT scan consists of hundreds of slices, and the number of lung cancer patients is also very high, due to which there is a huge burden on radiologists, especially in undeveloped or underdeveloped countries where there are not enough medical experts to examine the cancer imaging tests. To reduce this burden and to provide a second opinion to the doctors, several researchers have proposed different image processing and deep learning techniques for lung cancer detection and analysis. First step in automatic lung cancer detection is tumor segmentation, and if the tumor is segmented correctly then only it can be analyzed in a much better sense.
The Bioengineer’s Obligations to Patients
Published in Michael Davis, Engineering Ethics, 2017
The status of bioengineers is similar to that of nurses, in that both have a distinct body of professional knowledge and also stand outside the physician's primary relationship to the patient. Nurses, however, have their own professional–client relationship with the patient and an established code of ethics that governs that relationship and their relationship to physicians. Bioengineers have no such independent professional relationship to patients, nor are there established protocols to guide their interactions with respect to patients or physicians. Although their role is closest to that of a consultant (in the situation described above), it is much more informal, lacking the formal apparatus of fees, referrals, and the like. While other physicians may establish a professional relationship with a patient seeking a second opinion, no such option is presently established for bioengineers.
Understanding Conscientious Objection and the Acceptability of its Practice in Primary Care
Published in The New Bioethics, 2023
Savulescu views CO as conflicting with professionalism, in relation to a commitment to provide what is allowed by law (Savulescu 2006, p. 294). He argues that where society has endorsed a procedure legally, it becomes a right for citizens to receive it. Quoting Charo, Savulescu underlines the importance of fulfilling one’s duty (p. 295). However, as professional skills and opinions vary, Charo explains that having a collective obligation, rather than an individual duty to ensure non-discriminatory access to all professional services, allows individual HCPs the freedom of conscience to refrain from a procedure. There is a delicate balance between granting a right to patients, and imposing duties on HCPs, which needs to be further explored. Personal freedoms, as accorded by a tolerant society apply to HCPs, as well as patients. It would require a system for counselling and informing patients, to ensure access to care (Charo 2005, p. 2473). In General Practice and other settings, potentially controversial refusals could all be covered by teamwork.7 Patients should be informed of their right to seek a second opinion (GMC 2020, para. 13). The WMA does not require direct referrals but only recommends that physicians ‘provide sufficient information to enable the patient to initiate such a consultation in a timely manner’ (WMA 2022, p. 29). This is precisely the policy with regards to abortion in Canada (ARCC 2020, p. 2).
Presentation mode matters: examining how patients and healthcare professionals present content text during online health advice interaction
Published in Behaviour & Information Technology, 2023
Xitong Guo, Bangan Wu, Zhi Yang, Li Hou, Zhanfeng Zhu
Patients' online advice seeking is like searching for a second opinion. A second opinion is a consultation in which the patient seeks supplementary information and treatment insights regarding a diagnosis, and it helps patients make treatment decisions (Moumjid et al. 2007). Similarly, patients may seek advice online before going to hospitals offline or paying for an online consultation. There are slight differences between advice seeking online and second opinion. Second opinion usually takes place after a formal diagnosis, while advice seeking online can take place either before or after a more formal diagnosis.