Artificial Intelligence in Cancer: Diagnostic to Tailored Treatment

Cover
ARTIFICIAL
INTELLIGENCE
IN CANCER:
DIAGNOSTIC TO
TAILORED
TREATMENT
Copyright
Dedication
Foreword
Preface
1
Life challenge. Cancer
	Cancer throughout history
	Where are we now?
		Statistical assessment of research
			False positive and false negative
			p-Level
			Power analysis
			The Normal (Gaussian) distribution XN(μ,σ2)
			Kolmogorov-Smirnov test for Normal distribution
			Lilliefors test
			Shapiro-Wilk W test
			t-Test or Students t-test
			One group of observations t-test
			The sign test
			The Wilcoxon signed rank sum test
			Two groups of paired observations
			Two independent groups of observations
			Mann-Whitney test
			F test
			Levenes test
			Bartletts test
			One way ANOVA
			z-Test
				One sample z-test
				Two proportion z-test
			χ2 test
			Bayes theorem
				Kolmogorovs axioms
		How to read statistical tables
	Hope is around the corner. Artificial Intelligence steps in
	References
	Further reading
2
The beginnings
	Doctor's suspicion. Doctor+artificial intelligence combo's diagnosis
		Artificial neural networks
		Multiple linear regression
		Logistic regression
		Softmax classifier
		Learning paradigms
		The backpropagation algorithm
		Evolutionary computation learning paradigm
		Crossover or recombination
		Mutation
		Bayesian learning paradigm
		Radial basis function neural networks
		Extreme learning machine
		Adaptive single layer feedforward neural network
		ELM/ant colony optimization hybrid
		Ant colony optimization feature selection algorithm
		Probabilistic neural networks
		Deep learning/convolutional neural networks
		k-Nearest neighbor
		Clustering
		Non-hierarchical clustering
		Hierarchical clustering
	World collapses. Making an informed decision
	References
	Further reading
3
Pathologist at work
	Building the tumor's pattern
	Artificial Intelligence and histology
		Cox regression model
	Artificial Intelligence and immunohistochemistry
	Artificial Intelligence and genetics
	References
	Further reading
4
Surgeon at work
	Learning everything about the tumor: Tumor profiling
	Making a clean cut with the help of Artificial Intelligence
	References
5
Oncologist at work
	Establishing a treatment plan. Oncological guides
	Chemotherapy and Artificial Intelligence
		Support vector machines
	References
6
Radiotherapist at work
	Establishing a treatment plan
	Radiotherapy and Artificial Intelligence
	References
7
Survival analysis
	Kaplan-Meier survival curve
	Life tables
		The logrank test
		The hazard ratio
		Nelson Aalen Filter
	Survival regression
	The exponential distribution
	Poisson process
	The log normal distribution
	The Weibull distribution
	The log logistic distribution or Fisk distribution
	Gamma distribution
	The Gompertz distribution
	References
	Further reading
8
Remission and recurrence. What do to next?
	Decision trees
		Hunt's algorithm
		GINI index
		Entropy
		Misclassification measure
	Self organizing maps or Kohonen networks
	Cluster network
	References
9
Artificial Intelligence in cancer: Dreams may come true someday
	References
Index
	A
	B
	C
	D
	E
	F
	G
	H
	I
	K
	L
	M
	N
	O
	P
	R
	S
	T
	U
	V
	W
	X
	Z
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