Technology is in the process of completely transforming all aspects of 4 industries – construction, medicine, retail, and transport – with a significant reduction in the need for human labor. Here is the impact on Medicine, where, within 10-20 years (or less), it is reasonable to expect that:
- Most diseases will be eradicated (although some new ones may develop).
- We will be wearing sensors that constantly monitor our health, and immediately start a remedial process when something is wrong (from ordering medications, to booking an appointment with a medical specialist, or dispatching an ambulance).
- Medication dosage and anesthetics will be customized for our personal situation (weight, age, medical history, genetic makeup, etc.)
- Medication will be delivered to the most effective part of our bodies at the required frequency and dosage, using automatic dispensers, attached externally, or internally using nanobots.
- All medical testing (bloodwork, imaging, etc.) will be automated, with analyses confirmed (at least for a while) by specialists who may reside remotely.
- All surgery will be minimally invasive or replaced by the use of nanobots. Some surgery will be performed remotely (as the Da Vinci Surgical System has been doing since 2000).
- Defective organs will be replaced by transplants built from our own stem cells.
- Limbs and eyes will be replaced by brain-controlled prosthetics that operate more effectively than human versions. (The $6 Million Dollar Man and the Bionic Woman may no longer be fiction!)
- Living to an age of 130-150 years will be normal with a good quality of life.
The technologies, which will make this vision a reality, include AI, Robotics, Nanotechnology, and Biotechnology (gene editing via CRISPR-Cas9 with its enormous potential and considerable dangers).
The impact of these technologies on the medical profession is considerable. As with all professions, lower-level functions will be replaced by automation, but so will many specialists. There is already a suggestion that medical schools stop training radiologists (see below) as the ability of AI routines to analyze medical images is starting to match that of specialists, and will soon exceed it. As the above vision starts to be implemented, the need for general practitioners will reduce. (From as far back as 1979, studies have shown that people are more honest in responding to computer terminals – or robots – than to nurses or GPs.)
The jobs in the medical profession that will likely last longer are those requiring direct patient contact. So psychiatrists and psychologists will be around for the foreseeable future, and may be more in demand as society learns to cope with a world without paid work. (On the other hand, a client of Nick’s was developing a computer-based program to provide cognitive behavioral therapy about 15 years ago.). While the need for nurses and administrators in doctors’ offices will disappear, nurses will still be needed to provide hospital and community patient care.
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AI and the NHS: How AI will change everything for patients and doctors (AI/Dermatology - 2018-11 - ZDNet)
Healthcare: 5 digital trends for 2019 and beyond (AI/Dermatology - 2018-11 - Technology.org)
Stanford researchers create algorithm to interpret chest x-rays (AI/Dermatology - 2018-11 - Technology.org)
Google AI claims 99% accuracy in metastatic breast cancer detection (AI/Dermatology - 2018-10 - VentureBeat)
A new wave of chatbots are replacing physicians and providing frontline medical advice (AI/Dermatology - 2018-10 - MIT Technology Review)
AI algorithm used to adjust treatment dosages for metastatic cancer (AI/Dermatology - 2018-10 - Technology.org)
Machine learning outperforms clinicians in predicting outcomes for people at risk of psychosis and depression (AI/Dermatology - 2018-09 - Technology.org)
New AI system detects hard-to-spot cancerous lesions (AI/Dermatology - 2018-08 - Technology.org)
Big data and Deep Learning used to predict the fate of inpatients (AI/Dermatology - 2018-08 - ZDNet)
AI Neural network matches human cardiologists in detecting heart attacks (AI/Dermatology - 2018-07 - MIT Technology Review)
AI is better than dermatologists at diagnosing skin cancer (AI/Dermatology - 2018-05 - ScienceBlog)
Diagnostic imaging computers outperform human counterparts (AI/Diagnosis - 2018-04 - Case Western Daily)
• Diagnosing heart failure: 97% accuracy c.f. 74% for two pathologists.
• Distinguishing benign from malignant lung nodules on CAT scans: 5-8% superior to two human experts.
• Prostate cancer scans: computational imaging algorithms detected cancer in an MRI scan in >70% of cases where radiologists missed and correctly detected no cancer in 50% of cases where radiologists reported cancer.