Results 31 to 40 of about 3,116,882 (359)
The Dimensions of Tokenism in Patient and Family Engagement: A Concept Analysis of the Literature
Patient engagement (PE) has become embedded in discussions about health service planning and quality improvement, and the goal has been to find ways to observe the potential beneficial outcomes associated with PE.
Umair Majid MSc, MEd
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Patient-derived organoid (PDO) platforms to facilitate clinical decision making
Based on recent advances in organoid research as well as the need to find more accurate models for drug screening in cancer research, patient-derived organoids have emerged as an effective in vitro model system to study cancer.
Lisa Liu +4 more
semanticscholar +1 more source
Objective: Patients with relapsed ovarian cancer are offered multiple treatment options. To match treatment with the individual patient's life situation and preferences, healthcare professionals can apply shared decision making (SDM) including patient ...
Christian Nielsen Wulff +7 more
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Rethinking clinical decision-making to improve clinical reasoning
Improving clinical reasoning techniques is the right way to facilitate decision-making from prognostic, diagnostic, and therapeutic points of view. However, the process to do that is to fill knowledge gaps by studying and growing experience and knowing ...
S. Corrao, C. Argano
semanticscholar +1 more source
Transcranial alternating current stimulation (tACS) is a non-invasive brain stimulation technique that allows interaction with endogenous cortical oscillatory rhythms by means of external sinusoidal potentials.
Ivan Pozdniakov +4 more
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Genomic Profiling for Clinical Decision Making in Lymphoid Neoplasms.
With the introduction of large-scale molecular profiling methods and high-throughput sequencing technologies, the genomic features of most lymphoid neoplasms have been characterized at an unprecedented scale.
L. de Leval +71 more
semanticscholar +1 more source
Predictive models for clinical decision making: Deep dives in practical machine learning
The deployment of machine learning for tasks relevant to complementing standard of care and advancing tools for precision health has gained much attention in the clinical community, thus meriting further investigations into its broader use.
S. Eloranta, Magnus Boman
semanticscholar +1 more source
Stroke remains one of the leading causes of various disabilities, including debilitating motor and language impairments. Though various treatments exist, post-stroke impairments frequently become chronic, dramatically reducing daily life quality, and ...
Maxim Ulanov, Yury Shtyrov
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Unremarkable AI: Fitting Intelligent Decision Support into Critical, Clinical Decision-Making Processes [PDF]
Clinical decision support tools (DST) promise improved healthcare outcomes by offering data-driven insights. While effective in lab settings, almost all DSTs have failed in practice. Empirical research diagnosed poor contextual fit as the cause.
Qian Yang, Aaron Steinfeld, J. Zimmerman
semanticscholar +1 more source
Accessing Artificial Intelligence for Clinical Decision-Making
Advancements in computing and data from the near universal acceptance and implementation of electronic health records has been formative for the growth of personalized, automated, and immediate patient care models that were not previously possible ...
C. Giordano +5 more
semanticscholar +1 more source

