Advanced Diagnostics With Artificial Intelligence and Machine Learning in the Healthcare Sector DOI
Nilanjana Sarkar, Sumit Goel, Alex Khang

et al.

Advances in medical diagnosis, treatment, and care (AMDTC) book series, Journal Year: 2024, Volume and Issue: unknown, P. 47 - 81

Published: Jan. 5, 2024

Artificial intelligence (AI) systems are software (and possibly also hardware) designed by humans that, given a complex goal, act in the physical or digital dimension perceiving their environment through data acquisition, interpreting collected structured unstructured data, reasoning on knowledge, processing information, derived from this and deciding best action(s) to take achieve goal. for health includes machine learning (ML), natural language (NLP), speech recognition (text-to-speech speech-to-text), image vision, expert (a computer system that emulates decision-making ability of human expert), robotics, planning, scheduling, optimization. ML is core component AI allows automatically learn improve without being explicitly programmed. Computer programs access use it with aim intervention assistance adjust actions accordingly.

Language: Английский

Reshaping the healthcare world by AI-integrated wearable sensors following COVID-19 DOI
Bangul Khan,

Rana Talha Khalid,

Khair Ul Wara

et al.

Chemical Engineering Journal, Journal Year: 2025, Volume and Issue: 505, P. 159478 - 159478

Published: Jan. 11, 2025

Language: Английский

Citations

2
COVID-19 Early Detection in Doctors and Healthcare Workers (CEDiD) study: a cohort study on the feasibility of wearable devices DOI Creative Commons
Alexander Zargaran, Sara Sousi, Gary Colville

et al.

BMJ Open, Journal Year: 2025, Volume and Issue: 15(4), P. e089598 - e089598

Published: April 1, 2025

Background Infectious agents such as SARS-CoV-2 require strategies to contain outbreaks, particularly in hospitals where the spread of infection is most likely. Biometric monitoring heart rate, temperature, oxygen saturations and sleep might provide important early warning signs for SARS-CoV-2. This study aimed determine whether a smart medical device (E4 wristband) pulse oximeter used continuously measure skin temperature saturation would predict onset infection. Methods A single-centre, prospective observational cohort 30 healthcare workers (HCWs) working areas at high risk exposure were enrolled. HCWs tested using RT-qPCR daily self-administered swabs days. Each participant was asked wear an E4 wristband changes their throughout study. Results Nine (30%) (median (range) age 39 (27–57) years) positive COVID-19. No significant differences found pre-infection post-infection variations rate (p=0.31) or (p=0.44). Seven nine subjects reported symptoms some point during period: unusual fatigue (40%), headache (33%) runny nose (22%) frequent. Analysis trends observations demonstrated fluctuations biometric parameters. Conclusion These results suggest that wearable technology be useful documenting exposed HCWs. Trial registration number NCT04363489 .

Language: Английский

Citations

0
Artificial Intelligence and Machine Learning in Healthcare DOI
Nilanjana Sarkar, Sumit Goel

Advances in bioinformatics and biomedical engineering book series, Journal Year: 2024, Volume and Issue: unknown, P. 12 - 46

Published: March 4, 2024

Artificial intelligence (AI) systems are designed by humans that, given a complex goal, act in the physical or digital dimension perceiving their environment through data acquisition, interpreting collected structured unstructured data, reasoning on knowledge, processing information, derived from this and deciding best action(s) to take achieve goal. It is precisely AI's ability carry out speedy analysis of datasets that one its key strengths. The recent renaissance AI largely has been driven successful application deep learning — which involves training an artificial neural network with many layers (that is, ‘deep' network) huge datasets. rise dissemination clinical medicine will refine our diagnostic accuracy rule-out capabilities. In Book Chapter, we focus applications could augment change practice, identify impact arising development suggest future research directions.

Language: Английский

Citations

1
Designing a Hybrid Energy-Efficient Harvesting System for Head- or Wrist-Worn Healthcare Wearable Devices DOI Creative Commons

Zahra Tohidinejad,

Saeed Danyali, Majid Valizadeh

et al.

Sensors, Journal Year: 2024, Volume and Issue: 24(16), P. 5219 - 5219

Published: Aug. 12, 2024

Battery power is crucial for wearable devices as it ensures continuous operation, which critical real-time health monitoring and emergency alerts. One solution long-lasting energy harvesting systems. Ensuring a consistent supply from variable sources reliable device performance major challenge. Additionally, integrating components without compromising the wearability, comfort, esthetic design of healthcare presents significant bottleneck. Here, we show that with meticulous using small highly efficient photovoltaic (PV) panels, compact thermoelectric (TEG) modules, two ultra-low-power BQ25504 DC-DC boost converters, battery life can increase 9.31 h to over 18 h. The parallel connection converters at points output allows both individually achieve maximum point tracking (MPPT) during charging. We found under specific conditions such facing sun more than hours, became self-powered. Our results demonstrate long-term stable sensor node an efficiency 96%. Given high-power density solar cells outdoors, combination PV TEG harvest quickly sufficiently sunlight body heat. form factor system environmental particular occupations oil gas industry make suitable wearables worn on head, face, or wrist region, targeting outdoor workers.

Language: Английский

Citations

1
Advanced Diagnostics With Artificial Intelligence and Machine Learning in the Healthcare Sector DOI
Nilanjana Sarkar, Sumit Goel, Alex Khang

et al.

Advances in medical diagnosis, treatment, and care (AMDTC) book series, Journal Year: 2024, Volume and Issue: unknown, P. 47 - 81

Published: Jan. 5, 2024

Artificial intelligence (AI) systems are software (and possibly also hardware) designed by humans that, given a complex goal, act in the physical or digital dimension perceiving their environment through data acquisition, interpreting collected structured unstructured data, reasoning on knowledge, processing information, derived from this and deciding best action(s) to take achieve goal. for health includes machine learning (ML), natural language (NLP), speech recognition (text-to-speech speech-to-text), image vision, expert (a computer system that emulates decision-making ability of human expert), robotics, planning, scheduling, optimization. ML is core component AI allows automatically learn improve without being explicitly programmed. Computer programs access use it with aim intervention assistance adjust actions accordingly.

Language: Английский

Citations

0