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Development of Smart Surgical Assistants
Published in Jeff J. H. Kim, Richard Um, Rajiv Iyer, Nicholas Theodore, Amir Manbachi, Design and Development of Smart Surgical Assistant Technologies, 2022
Jeff J. H. Kim, Richard Um, Rajiv Iyer, Nicholas Theodore, Amir Manbachi
Nuance's Dragon Ambient eXperience or the Ambient Clinical Intelligence (ACI) service frees physicians from taking notes during patient appointments, allowing them to interact more personally with patients. The ACI works by simply transcribing the conversation between patient and physician. It also organizes the patient's symptoms and, using its AI algorithm, creates a differential diagnosis by contextualizing the conversation. This benefits physicians in two ways. First, patient interactions become more fluid. There are no pauses or interruptions between conversations as the provider jots down notes. This not only saves time but also allows patients to speak uninterrupted. Second, the ACI allows physicians to focus on the patient by eliminating the accessory task that dragged them down during these appointments. Pen and paper or monitor and keyboard are no longer the center of the interaction, and physicians are able to maintain good eye contact and attentive body language. Furthermore, patient information that was previously overlooked due to time and focus constraints can be given ample attention. Doctors can spend more time listening to patients' stories, backgrounds, and socioeconomic conditions and then can deliver a holistic treatment plan.
Artificial Intelligence in Medical Imaging
Published in P. Kaliraj, T. Devi, Artificial Intelligence Theory, Models, and Applications, 2021
InterpretationAI assistants working in the background can alert the radiologists to check the missing findings. It can also be used to detect recurring secondary findings.DL algorithms have already been demonstrated to detect Alzheimer’s disease and mild cognitive impairment.A combination of threshold-based detection and ML-based classification has been addressed to evaluate 18F-NaF PET/CT scans for bone metastases in prostate cancer patients.ML algorithms are used in 18F-FDG PET to estimate the arterial input function to quantify regional cerebral metabolic rate for glucose.AI systems can support the interpreter in the process of classification and differential diagnosis.
Diffusion Magnetic Resonance Imaging in the Central Nervous System
Published in Shoogo Ueno, Bioimaging, 2020
Kouhei Kamiya, Yuichi Suzuki, Osamu Abe
Although the formulation is simple, ADC and diffusion-weighted images dramatically improved clinical image-based diagnoses of neurological diseases (Citton et al., 2012; O’Connor et al., 2013). They provide information that directly alters clinical management by identifying lesions that would otherwise have been undetected or by narrowing the list of differential diagnoses. First, in 1990, a profound decrease in ADC and hyperintensity on diffusion-weighted images were discovered to reflect acute cerebral ischemia (Moseley et al., 1990). The diffusion abnormalities can be seen approximately one hour after the insult – hours before computed tomography or other MR sequences show changes. Since then, ADC and diffusion-weighted images have been shown to be useful in characterizing brain lesions, including abscess, encephalitis, prion disease, tumors, secondary degeneration, demyelination, metabolic, drug- or toxin-induced encephalopathies, and status epilepticus, among others. This list is still evolving, with continuing discoveries and establishment of previously unrecognized disease entities (Konno et al., 2018; Sone et al., 2016; Takanashi, 2009).
Mitigating cognitive bias with clinical decision support systems: an experimental study
Published in Journal of Decision Systems, 2023
Alisa Küper, Georg Lodde, Elisabeth Livingstone, Dirk Schadendorf, Nicole Krämer
The range of ways CDSS can support physicians is vast: including but not limited to support in form of alarm systems, disease management, prescription, drug control, and diagnostics (Sutton et al., 2020). One possible clinical support system is a differential diagnosis decision support system that assists physicians in the diagnostic process by generating differential diagnoses from information previously fed into the system (McParland et al., 2019; Müller et al., 2019). Entering clinical findings, patient history and demographic data offers a list of potential diagnoses. By providing a second diagnostic opinion, the system offers the opportunity to the physician to adjust a first diagnostic decision based on additional data (Jussupow et al., 2021). Shared decision-making assisted by a decision support system is suggested to be a useful tool in mitigating negative effects of bias and heuristics, without putting more strain on additional physicians as decision-makers (Thomas et al., 2021).
Optimal metric for condition rating of existing buildings: is five the right number?
Published in Structure and Infrastructure Engineering, 2019
Félix Ruiz, Antonio Aguado, Carles Serrat, Joan R. Casas
In the context of the built environment, the level of certainty to assign values will not be a priori very high, since to assess the degree of damage of a component (either a beam, a balcony, a cornice, a bearing wall) may be subject to subjectivity. Therefore, the scales that a priori can be more useful for our proposal are the Modified Mercalli scale, the VAS scale, the Norton scale and the Glasgow scale, especially the last 3 (associated with the field of medicine), since they have also some degree of uncertainty when assigning values in the diagnosis of people, some of them in emergency conditions. The field of medicine has important conceptual similarities with the field of diagnosis of building elements. Some of the similarities between diagnosis of human beings and diagnosis of buildings are the next ones: To propose appropriate cure it is necessary first to develop an accurate diagnosis, in order to find out the causes of any disfunctions.The conceptual techniques to develop diagnosis in both scopes are similar, based on differential diagnosis methodology.The main goal is the same: restore the health (of the human being or of the building).Similar words are used: diagnosis, rehabilitation, therapy, etc.Both fields use similar diagnostic tools: endoscopy, X ray, ultrasonic techniques, magnetic flux, etc.
Detection of Monkeypox from skin lesion images using deep learning networks and explainable artificial intelligence
Published in Applied Mathematics in Science and Engineering, 2023
Tushar Nayak, Krishnaraj Chadaga, Niranjana Sampathila, Hilda Mayrose, G. Muralidhar Bairy, Srikanth Prabhu, Swathi S. Katta, Shashikiran Umakanth
While the usage of polymerase chain reaction tests (PCR Tests) is the recommended modality of Monkeypox diagnosis, the infrastructure required in the testing of Monkeypox could be a hindering factor in rural areas [9]. They also take a considerable amount of time and are also prone to false negative results. Therefore, differential diagnosis can be used with the help of the skin lesions that form the basis of the work discussed below and our proposed modality. Table 1 compares the onset of skin lesion images in monkeypox, chickenpox and measles patients. Combining the differential diagnosis could be cost-effective and time-efficient.