RESUMEN
Background: Artificial intelligence technology can be applied in several aspects of healthcare delivery and its integration into the Nigerian healthcare value chain is expected to bring about new opportunities. This study aimed at assessing the knowledge and perception of healthcare professionals in Nigeria regarding the application of artificial intelligence and machine learning in the health sector. Methods: A cross-sectional study was undertaken amongst healthcare professionals in Nigeria with the use of a questionnaire. Data were collected across the six geopolitical zones in the Country using a stratified multistage sampling method. Descriptive and inferential statistical analyses were undertaken for the data obtained. Results: Female participants (55.7%) were slightly higher in proportion compared to the male respondents (44.3%). Pharmacists accounted for 27.7% of the participants, and this was closely followed by medical doctors (24.5%) and nurses (19.3%). The majority of the respondents (57.2%) reported good knowledge regarding artificial intelligence and machine learning, about a third of the participants (32.2%) were of average knowledge, and 10.6% of the sample had poor knowledge. More than half of the respondents (57.8%) disagreed with the notion that the adoption of artificial intelligence in the Nigerian healthcare sector could result in job losses. Two-thirds of the participants (66.7%) were of the view that the integration of artificial intelligence in healthcare will augment human intelligence. Three-quarters (77%) of the respondents agreed that the use of machine learning in Nigerian healthcare could facilitate efficient service delivery. Conclusion: This study provides novel insights regarding healthcare professionals' knowledge and perception with respect to the application of artificial intelligence and machine learning in healthcare. The emergent findings from this study can guide government and policymakers in decision-making as regards deployment of artificial intelligence and machine learning for healthcare delivery.
RESUMEN
Cellulose is a non-toxic, bio-degradable, and renewable biopolymer which is abundantly available in nature. The most common source of commercial microcrystalline cellulose is fibrous wood pulp. Cellulose and its derivatives have found wide commercial applications in the pharmaceutical, cosmetic, food, paper, textile, and engineering industries. This study aims to isolate and characterize cellulose forms from cocoa pod husk (CPH) and to assess its mechanical and disintegration properties as a direct compression excipient in metronidazole tablets. Two isolated cellulose types (i.e., cocoa alpha-cellulose (CAC) and cocoa microcrystalline cellulose (C-MCC)) were compared with avicel (AV). CAC and C-MCC were characterized for their physicochemical properties using Scanning Electron Microscopy (SEM), FTIR spectroscopy, Differential Scanning Calorimetry (DSC), and X-Ray Powder Diffraction (XRD). Metronidazole tablets were produced by direct compression with cellulose. The mechanical and disintegration properties of the tablets were evaluated. CAC and C-MCC yield was 42.3% w/w and 38.25% w/w, respectively. Particle diameters were significantly different with CAC (282.22 µm) > C-MCC (161.32 µm) > AV (72.51 µm). CAC and C-MCC had a better flow than AV. SEM revealed the fibrous nature of the cellulose. FTIR and XRD analysis confirmed the presence of cellulose with crystallinity index of 69.26%, 43.83%, and 26.32% for AV, C-MCC, and CAC, respectively. C-MCC and AV are more crystalline and thermally stable at high temperatures compared to CAC. The mechanical and disintegration properties of C-MCC and AV tablets complied with pharmacopeia specifications. Taken together, C-MCC isolated from CPH displayed some fundamental characteristics suitable for use as a pharmaceutical excipient and displayed better properties compared to that of AV.