Artificial Intelligence and Machine Learning (ML) are increasingly being used in the Neurocritical Care and healthcare in
general. The ML model algorithms have many existing and potential uses in triage, diagnosis, clinical decision support, mon
itoring, and prevention of clinical syndromes. Combining and appropriately analyzing the vast number of neurocritical care
data parameters, ranging from clinical (including electronic medical record), laboratory, imaging, multimodal monitoring,
and many others is beyond human capability. ML algorithms can help the providers and patients in analyzing these data pa
rameters to address certain defined problems. Machine learning does have limitations in several aspects (technical, medi
co-legal, financial, clinical, ethical, social, etc.), which can prevent realization of its full potential. Addressing these pitfalls
with appropriate solutions in a timely manner is important to get the maximum benefit out of this valuable technological ad
vancement
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- Predictors of Obstructive Sleep Apnea Risk among Blacks with Metabolic Syndrome
- Acculturation and Subclinical Atherosclerosis among U.S. South Asians: Findings from the MASALA study
- Wake-up Strokes Are Similar to Known-Onset Morning Strokes in Severity and Outcome
- Endothelial Cells May Have Tissue-Specific Origins
- Molecular Mechanism Linking BRCA1 Dysfunction to High Grade Serous Epithelial Ovarian Cancers with Peritoneal Permeability and Ascites
- Objectively Coding Intervention Fidelity During A Phone-Based Obesity Prevention Study
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Recent Articles
The Effect of Music on Decreasing of Adaptation Difficulty in Alzheimer’s Patients: Randomized Controlled Study
Objective: This study was explored the impact of Nihavent theme on decreasing of adaptation difficulty in patients with
Alzheimer’s disease.
Materials and methods: The study was conducted with a total of 30 patients, 15 patients in the intervention group and 15
patients in the control group. Before the application, The Descriptive Characteristics Data Form and Assessment Scale of
Adaptation Difficulty for the Elderly were administered to both groups. The patients in intervention group had music ses
sions for 12 weeks. Patients in the control group received standard care but did not participate in the specific intervention.
One week after the music session completed, the Assessment Scale of Adaptation Difficulty for the Elderly was re-adminis
tered to both groups.
Empowering Incarcerated Individuals: Solution-Focused Therapy for Reducing Tobacco Smoking Dependency Behaviour among Correctional Inmates in Oyo State, Nigeria
This study examined the effectiveness of Solution-Focused Therapy (SFT) in reducing tobacco smoking dependency be
haviour among incarcerated individuals within correctional settings in Oyo State. Anchored on social cognitive theory,
which highlights the role of self-efficacy in behaviour change, the research was designed to address the pressing public
health concern of tobacco smoking among the inmates.
Normative Anthropometric Analysis of Linear Body Dimensions: A Prospective Approach to the Design of Negroid Anatomical Models
Aim: The aim of this study was to generate linear anthropometric data for the design of Negroid anatomical model for fu
ture standardization.
Method: The research design was cross-sectional and non-experimental design. A total number of three hundred (300) sub
jects were recruited between the ages of 18 to 37 years with a BMI range of 18.50 to < 30.00 for this study. Taro Yamane’s
formula was used to determine the minimum sample size. BMI and linear body anthropometric measurements were taken
using a stadiometer, calibrated flexible meter tape, meter rule, and weighing scale. Data were analyzed using SPSS for dis
crete statistics and t-tests of significance